Upload
others
View
4
Download
0
Embed Size (px)
Citation preview
Intercalibration of national methods
to assess the ecological quality of rivers in Europe
using benthic invertebrates and aquatic flora
Inaugural-Dissertation
zur Erlangung des Doktorgrades
Dr. rer. nat.
des Fachbereichs
Biologie und Geografie
an der
Universität Duisburg-Essen
vorgelegt von
Sebastian Birk
geboren in Bottrop
April, 2009
Die der vorliegenden Arbeit zugrunde liegenden Experimente wurden in der Abteilung
für Angewandte Zoologie/Hydrobiologie der Universität Duisburg-Essen durchgeführt.
1. Gutachter: Prof. Dr. Daniel Hering
2. Gutachter: Prof. Dr. Bernd Sures
3. Gutachter: Prof. Dr. Jürgen Böhmer
Vorsitzender des Prüfungsausschusses: Prof. Dr. Perihan Nalbant
Tag der mündlichen Prüfung: 15. Oktober 2009
“
c
h
a
w
a
s
Her
With a thousand eyes, the river looked at him, with green ones, with white ones, with
rystal ones, with sky-blue ones. How did he love this water, how did it delight him,
ow grateful was he to it! In his heart he heard the voice talking, which was newly
waking, and it told him: Love this water! Stay near it! Learn from it! Oh yes, he
anted to learn from it, he wanted to listen to it. He who would understand this water
nd its secrets, so it seemed to him, would also understand many other things, many
ecrets, all secrets.”
mann Hesse: Siddhartha – An Indian Tale
Table of contents
Table of contents
Preface........................................................................................................................................11
1 Direct comparison of assessment methods using benthic macroinvertebrates: a contribution to the EU Water Framework Directive intercalibration exercise ..........15
1.1 Introduction .............................................................................................................................. 15 1.2 Methods ................................................................................................................................... 16 1.2.1 Overview ......................................................................................................................................... 16 1.2.2 Samples and sites........................................................................................................................... 17 1.2.3 National assessment methods and quality classifications ............................................................... 18 1.2.4 Data preparation ............................................................................................................................. 19 1.2.5 Correlation and regression analysis ................................................................................................ 21 1.2.6 Comparison of quality class boundaries.......................................................................................... 21 1.3 Results ..................................................................................................................................... 22 1.3.1 Definition of reference values.......................................................................................................... 22 1.3.2 Descriptive statistics of national indices calculated from the AQEM-STAR datasets ...................... 22 1.3.3 Correlation and regression of national assessment methods.......................................................... 22 1.3.4 Correlation to environmental gradients (PCA)................................................................................. 24 1.3.5 Comparison of national quality classes ........................................................................................... 25 1.4 Discussion................................................................................................................................ 30 1.4.1 Role of reference conditions in the intercalibration exercise ........................................................... 30 1.4.2 Relations between assessment methods ........................................................................................ 30 1.4.3 Comparison of class boundary values ............................................................................................ 32 1.4.4 When shall boundaries be considered as different?........................................................................ 33 1.5 Conclusions ............................................................................................................................. 34
2 Intercalibration of assessment methods for macrophytes in lowland streams: direct comparison and analysis of common metrics ..................................................36
2.1 Introduction .............................................................................................................................. 36 2.2 Methods ................................................................................................................................... 37 2.2.1 Samples and sites........................................................................................................................... 37 2.2.2 National assessment methods and quality classifications ............................................................... 38 2.2.3 Description of biotic metrics analysed to provide “common macrophyte metrics” ........................... 39 2.2.4 Data preparation ............................................................................................................................. 40 2.2.5 Correlation and regression analysis: macrophyte assessment methods, potential common
metrics and pressure gradients ....................................................................................................... 40 2.2.6 Comparison of quality class boundaries.......................................................................................... 42 2.3 Results ..................................................................................................................................... 42 2.3.1 Comparison of classification schemes ............................................................................................ 42 2.3.2 Correlation and regression analysis ................................................................................................ 43 2.3.3 Direct comparison of quality class boundaries ................................................................................ 46 2.3.4 Indirect comparison of quality class boundaries using Ellenberg_N as common macrophyte
metric .............................................................................................................................................. 47 2.4 Discussion................................................................................................................................ 48 2.4.1 Testing of intercalibration approaches ............................................................................................ 49 2.4.2 Implications for the macrophyte intercalibration exercise................................................................ 52
Table of contents
3 Towards harmonization of ecological quality classification: establishing common grounds in European macrophyte assessment for rivers ..........................54
3.1 Introduction .............................................................................................................................. 54 3.2 Methods ................................................................................................................................... 56 3.2.1 Data basis ....................................................................................................................................... 56 3.2.2 National assessment methods ........................................................................................................ 57 3.2.3 Intercalibration analysis................................................................................................................... 59 3.3 Results ..................................................................................................................................... 62 3.4 Discussion................................................................................................................................ 64 3.4.1 Description of stream type-specific macrophyte communities......................................................... 64 3.4.2 Development of a common metric for intercalibration ..................................................................... 67 3.5 Conclusions ............................................................................................................................. 69
4 A new procedure for comparing class boundaries of biological assessment methods: a case study from the Danube Basin ...........................................................70
4.1 Introduction .............................................................................................................................. 70 4.2 Materials and Methods............................................................................................................. 73 4.2.1 National assessment methods and intercalibration common stream types ..................................... 73 4.2.2 Data ................................................................................................................................................ 74 4.2.3 Data analysis................................................................................................................................... 76 4.3 Results ..................................................................................................................................... 81 4.3.1 Selection of common metrics .......................................................................................................... 81 4.3.2 Data screening ................................................................................................................................ 81 4.3.3 Definition and application of benchmarks........................................................................................ 82 4.4 Discussion................................................................................................................................ 85 4.4.1 Objectives of boundary comparison and setting.............................................................................. 85 4.4.2 Rationale for selecting environmental parameters for benchmark definition ................................... 86 4.4.3 Consistent and verifiable definition of benchmarks ......................................................................... 88
Summary and conclusions.......................................................................................................90
Zusammenfassung....................................................................................................................97
References ...............................................................................................................................107
Appendix: Common type-specific mICM indicator taxa scores analysed in Chapter 3...121
List of tables
List of tables
Table 1: Overview of samples included in the analysis.............................................................................. 18
Table 2: Overview of national assessment methods (BI - Biotic Index, MI – Multimetric Index) ................ 19
Table 3: Original reference and class boundary values of the national assessment methods (abs – absolute value). .................................................................................................................................. 20
Table 4: Reference values of national assessment methods derived by using the 75th percentile of index values calculated from samples taken at high status sites. For small mountain streams the number of high status sites’ samples is individually specified in brackets. Values of lowland streams are based on 50 samples...................................................................................................... 22
Table 5: Descriptive statistics of national indices calculated from the AQEM-STAR datasets (normalized index values). .................................................................................................................. 23
Table 6: Coefficients of determination based on linear and nonlinear regression (p < 0.05) – (IMI-IC: Integrative Multimetric Index for Intercalibration (see text for explanation); PE1: pollution/eutrophication gradient; HY1: hydromorphological gradient)................................................ 26
Table 7: Coefficients of linear regression equations (a - slope, b - intercept) for the common scales and the abiotic gradients (IMI-IC: Integrative Multimetric Index for Intercalibration (see text for explanation); PE1: pollution/eutrophication gradient; HY1: hydromorphological gradient).................. 27
Table 8: EQR values of the high-good (H|G) and good-moderate (G|M) quality class boundaries transferred into “common scale”. In addition, the values of the abiotic gradients (PE1, HY1) corresponding to the national class boundaries are displayed. For each value derived by regression the 95 percent confidence interval is specified (IMI-IC: Integrative Multimetric Index for Intercalibration (see text for explanation); PE1: pollution/eutrophication gradient; HY1: hydromorphological gradient) ............................................................................................................. 28
Table 9: Comparison of the saprobic indicator taxa lists of Austria, Czech Republic, Germany and Slovak Republic: Share of common taxa and coefficients of determination derived from correlation analysis of indicator values and indicator weights............................................................. 29
Table 10: Overview of the sites surveyed at medium-sized lowland streams. ........................................... 37
Table 11: Range of trophic status covered by the dataset (n=108): descriptive statistics of the chemical parameters nitrate and total phosphorus ............................................................................. 38
Table 12: Overview of macrophyte assessment methods.......................................................................... 38
Table 13: Comparison of macrophyte abundance schemes ...................................................................... 39
Table 14: Class boundaries of the national assessment methods and derived reference values using the 95th percentile value of all survey sites (n.a. – not applicable). ..................................................... 40
Table 15: Metrics tested with the macrophyte dataset. For taxa assignment to growth forms refer to Table 18 (# taxa - number of taxa, % - relative abundance, ca - composition/ abundance, f - functional, rd - richness/diversity, st - sensitivity/tolerance). ............................................................... 41
Table 16: Correlation and regression analysis of macrophyte assessment methods, selected macrophyte metrics and environmental gradients: Type of correlation (pos. - positive, neg. - negative) and coefficients of determination (R2) based on linear and nonlinear regression. Nonlinear R2 is only given if providing higher coefficients of determination (p < 0.05; n.s. – not significant)........................................................................................................................................... 45
Table 17: EQR values of the high-good (H|G) and good-moderate (G|M) quality class boundaries transferred into MTR and Ellenberg_N scales via nonlinear regression analysis. For each value derived by regression the 95 percent confidence interval is specified (n.a. – not applicable). (1) f(x) = a + b·x1.5; (2) f(x) = a + b·x3........................................................................................................ 46
List of tables
Table 18: Reference taxa and disturbance indicating taxa of lowland streams and their growth forms (following van de Weyer 2003). .......................................................................................................... 51
Table 19: Characterisation of the common stream types........................................................................... 56
Table 20: Number of macrophyte surveys used in the analysis, listed per country and common stream type..................................................................................................................................................... 57
Table 21: Conversion table of national macrophyte abundance classes into the international abundance scale................................................................................................................................. 58
Table 22: National assessment methods using macrophytes in rivers....................................................... 59
Table 23: Level of aquaticity characterizing the affinity of the macrophyte taxon to water according to C. Chauvin (pers. comm.) ................................................................................................................... 60
Table 24: Range of Spearman’s correlation coefficients (CorrCoef) and taxa showing highest positive (+) and negative (-) correlation of abundance to the mean index gradient.......................................... 62
Table 25: Results of the linear regression analysis of mICM against the national metrics R2 (orig.) – coefficient of determination using national index with original indicator taxa list, R2 (amend.) – coefficient of determination using national index with amended indicator taxa list.............................. 63
Table 26: Number of common high status sites (N), mICM reference values (REF), and 5th and 10th percentile values of the mICM EQR distributions................................................................................ 63
Table 27: Definition of main terms dealt with in this chapter ...................................................................... 71
Table 28: National assessment methods for rivers using benthic diatoms and invertebrates. ................... 73
Table 29: Common stream types addressed in this study ......................................................................... 74
Table 30: The number of sites and samples per country and common intercalibration type, and number of taxa per sample ................................................................................................................. 75
Table 31: National methods for sampling and processing invertebrate samples ....................................... 75
Table 32: Environmental data collected at each sampling site .................................................................. 76
Table 33: Classification scheme to assess the hydromorphological quality status of invertebrate sampling sites ..................................................................................................................................... 77
Table 34: Threshold values of environmental parameters used to screen for diatom (DI, only type R-E4) and invertebrate (BI) sampling sites of high or good environmental status (n.a. = not applicable). ......................................................................................................................................... 79
Table 35: Maximum Spearman Rank correlation coefficients for environmental variables and common metrics from national datasets (n.s. = non-significant correlation; *p<0.05, **p<0.01, ***p<0.001)..... 81
Table 36: Quality class boundaries and near-natural reference values of the national diatom indices translated into diatom ICMi values (dICMi = diatom ICMi; TI-AT = Austrian Trophic Index; SI-AT = Austrian Saprobic Index; DI-SK = Slovak Diatom-Index; 95CI = 95 percent confidence interval of regression line). .................................................................................................................................. 82
Table 37: Biological class boundaries derived from regression analysis of the invertebrate ICMi against national indices (95CI = 95 percent confidence interval of regression line; * = class boundary defined as 20 percent deviation from predicted boundary value; ‡ = Confidence interval derived from regression analysis using ranks transformed into whole numbers (“1” = 1, “1 to 2” = 2, “2” = 3 etc.). .................................................................................................................................... 85
List of figures
List of figures
Figure 1: Regression of BMWP (PL) against SI (DE). Both linear (R2 = 0.53, dashed) and nonlinear (R2 = 0.63) regression lines are plotted. ............................................................................................. 24
Figure 2: Relative comparison of good-moderate class boundary values (incl. 95 percent confidence intervals) using IMI-ICR-C3 and corresponding chemical pressure values of the small siliceous mountain streams. Based on the results of the pressure data analysis two groups of similar boundaries are highlighted by dashed circles. .................................................................................... 34
Figure 3: Distribution of quality classes in the dataset resulting from four macrophyte assessment methods (H – high; G – good; M - moderate and worse). Quality classes of RI (DE) are based on the analysis of the Reference Index and additional criteria (Schaumburg et al., 2004). The class boundary between high/good (H+G) and moderate quality of MTR (UK) is based on recommendations for the interpretation of MTR scores to evaluate the trophic state (Holmes et al., 1999; see text for details).............................................................................................................. 43
Figure 4: Nonlinear regression of German RI (solid line; R2 = 0.28) and Dutch DMS (dashed line; R2 = 0.59) against the number of species................................................................................................... 44
Figure 5: Nonlinear regression of French IBMR (solid line; R2 = 0.77) and German RI (dashed line; R2 = 0.53) against British MTR. ............................................................................................................... 47
Figure 6: Nonlinear regression of French IBMR (solid line; R2 = 0.56), German RI (dashed line; R2 = 0.58) and British MTR (dotted line; R2 = 0.70) against Ellenberg_N. .................................................. 48
Figure 7: Map of Europe showing the locations of Austria (AT), Slovak Republic (SK), Hungary (HU), Romania (RO) and Bulgaria (BG). ...................................................................................................... 72
Figure 8: Overview of the analytical procedure.......................................................................................... 78
Figure 9: Calculation of benchmarks. Distribution of diatom (a, b) and invertebrate (c to f) common metric values at sites of good (A) or high (A*, Slovak R-E1) and worse (B) environmental status. Metrics were standardized by the quartile values marked with an arrow. Relevant quartiles between groups (A - B) are significantly different at p<0.001 (χ2-Test)............................................... 83
Figure 10: Boundary comparison. Translation of Austrian (TI-AT) and Slovak (DI-SK) good quality boundaries into comparable values of the diatom common metric (dICMi) by linear regression (dashed lines). White squares represent samples of good environmental status. .............................. 84
Figure 11: Setting the high-good class boundary for the Slovak invertebrate index (MMI-SK) using the biological benchmark (invertebrate ICMi = 1). White squares represent samples of high environmental status (R2 = coefficient of determination)..................................................................... 84
List of abbreviations
List of abbreviations
AQEM The Development and Testing of an Integrated Assessment System for the Ecological Quality
of Streams and Rivers throughout Europe using Benthic Macroinvertebrates (European
Research Project)
ASPT Average Score Per Taxon
AT Austria
BG Bulgaria
BMWP Biological Monitoring Working Party score
BOD Biological Oxygen Demand
CLC Corine Land Cover
CZ Czech Republic
DE Germany
DK Denmark
DMS Dutch Macrophyte Score
DSFI Danish Stream Fauna Index
EQR Ecological Quality Ratio
EU European Union
FR France
GD General Degradation Index
GIG Geographical Intercalibration Group
HU Hungary
IBMR Indice Biologique Macrophytique en Rivière
ICM Intercalibration Common Metric
ICMi Intercalibration Common Multimetric index
(EE ICMi=Eastern European ICMi, dICMi=diatom ICMi)
IMI-IC Integrative Multimetric Index for Intercalibration
IPS Indice de Polluosensibilité Spécifique
MTR Mean Trophic Rank
NL Netherlands
PCA Principal Components Analysis
PL Poland
R Correlation coefficient
R2 Coefficient of determination
R-C… Common intercalibration stream type of the Central-Baltic GIG
R-E… Common intercalibration stream type of the Eastern Continental GIG
RI Reference Index
RO Romania
SE Sweden
SI Saprobic Index
SK Slovak Republic
STAR Standardisation of River Classifications: Framework method for calibrating different biological
survey results against ecological quality classifications to be developed for the Water
Framework Directive (European Research Project)
TI Trophic Index
#fam Number of invertebrate families
%EPT Relative abundance of Ephemeroptera, Plecoptera and Trichoptera taxa
95CI 95 percent confidence interval of the regression line/curve
Acknowledgements
Acknowledgements
First sincere thanks go to Daniel Hering, my Ph.D. advisor and mentor in the various
facets of scientific life. His keen intellect was my role model for tackling the complex
questions of my work, and his pragmatism saved me valuable hours of theoretical
idling. Nigel Willby and Christian Chauvin introduced me to the mysterious worlds of
river macrophyte assessment. Our long discussions about Callitriche hamulata and
sandy lowland brooks also made even my dead-end efforts worthwhile. Moreover, I am
grateful for the enlightening experiences I made as a member of the Rivers
Intercalibration Steering Group. Especially Isabel Pardo, John Murray-Bligh, Roger
Owen, Jean-Gabriel Wasson, Martyn Kelly and Wouter van de Bund broadened my
horizon regarding the concepts of river ecology and their practical implementation. The
support of Jürgen Böhmer in all issues of intercalibration is also gratefully
acknowledged.
Further thanks are due to Ursula Schmedtje, who invited me to work with the
International Commission for the Protection of the Danube River. My challenging
cooperation with the colleagues from Eastern Europe were a pleasure and enriched my
work in various ways. In this regard I am especially grateful for the close collaboration
with Birgit Vogel.
Furthermore, I always appreciated the sound working atmosphere at the Department of
Applied Zoology/Hydrobiology. I like to express my sincere thanks to the colleagues
that supported me in many different ways: Thomas Korte, Christian Feld, Armin Lorenz,
Jelka Lorenz, Jörg Strackbein, Carolin Meier, Nadine Haus, Marta Wenikajtys and
Peter Rolauffs. My work significantly benefited from the discussions held among the
experts of the working group for river macrophyte intercalibration.
Finally, I like to thank my wife Inga, who always backed my ventures. I am also grateful
to my parents and grandparents for all their guidance and advice.
This work was financially supported by the 5th Framework Programme of the European
Commission, the German Working Group on Water Issues (LAWA), the German
Federal Environment Agency (UBA), and the UNDP Danube Regional Project.
Preface
Preface
The question “What should I do?“ is posed by Kant (1800) as one of the four principal
questions of philosophy. It addresses the broad field of ethics, encompassing right
conduct and good life. Its relevance was mainly recognized for the interpersonal
relations in social life. But with increasing awareness of the severe environmental
effects of human behaviour the relationship between man and the natural world was
brought into focus (Hardin, 1968, White, 1968). In this context Kant’s “What should I
do?” can thus be specified as “How do I have to behave towards the natural
environment?”. Ecology cannot answer this question as it implies normative statements
beyond the descriptive character of science (Hume, 1978, Valsangiacomo, 1998). Our
notion of the right conduct towards the environment forms part of the social discourse
and, as such, becomes manifest, for instance, in environmental policy. Here, it shapes
the moral background embedding the application of science.
The doctoral thesis at hand comprises applied science serving the implementation of
the European Water Framework Directive (WFD) (European Commission, 2000). This
comprehensive legislation establishes a framework for common action in the field of
water policy among the 27 Member States of the European Union. The WFD obliges
Member States to classify the ecological quality of their rivers, lakes, coastal waters
and estuaries. Countries are applying assessment methods to evaluate the status of
biological quality elements, i.e. selected groups of plants or animals inhabiting the
aquatic environment. These methods distinguish between different types of surface
waters, for instance small sandy lowland brooks or alpine streams with gravely
substrates, and classify water bodies within these types in either high, good, moderate,
poor or bad quality status. The WFD requires that all surface water bodies must
achieve good ecological quality status, determining this status through normative
definitions (European Commission, 2000, p. 38):
“
lo
th
c
The values of the biological quality elements for the surface water body type show
w levels of distortion resulting from human activity, but deviate only slightly from
ose normally associated with the surface water body type under undisturbed
onditions.”
11
Preface
This definition of good ecological status represents a key element of European water
policy. The Union commits its Member States to the right conduct towards the aquatic
environment and imposes restoration action if water bodies fail to achieve this
objective. The concept of good ecological quality is therefore of crucial importance in
the implementation of the WFD. However, the Directive leaves it to the Member States
to put this rather vague definition into practice: Thus, the individual countries are in
charge of developing national assessment methods and classifying the ecological
status of their water bodies. To compare and to harmonize the national interpretations
of good ecological status, the WFD stipulates an intercalibration exercise (Heiskanen et
al., 2004).
The purpose of intercalibration is to set a common level of ambition among Member
States in achieving the WFD’s objectives. Ideally, intercalibration must ensure that, for
instance, a German water body in good status according to the German assessment
method would be classified as “good” by the Dutch or Danish method, if the same
water body was located on a Dutch or Danish river. However, the biological
communities of surface waters differ between countries even within the same water
body type, under conditions not influenced by man. Furthermore, the national status
classifications are characterized by differing assessment concepts and traditions (Birk,
2003, Birk & Schmedtje, 2005). Regarding only the classification of rivers and lakes,
both undertaken using four biological quality elements (phytoplankton, phytobenthos
and macrophytes, benthic invertebrates, fish), more than 200 national assessment
methods have to be intercalibrated between the 27 Member States of the European
Union. This gives an idea of the difficult and complex character of intercalibration.
The scientific work presented in this thesis establishes the methodological basis for the
technical implementation of intercalibration. The fundamental question guiding the
entire research is: How can the definitions of good ecological status be best compared
between national assessment methods? Since all assessment methods employ
biological indices to classify the ecological status, investigating the correlations of these
indices is a primary task of intercalibration. According to the Directive, good status shall
“deviate only slightly from […] undisturbed conditions”. This statement highlights two
important aspects relevant for the comparison of national classifications: First,
undisturbed conditions form the reference point of ecological status assessment. And
12
Preface
second, good status is defined as a slight deviation from this reference. This thesis
looks into the role of reference conditions in the intercalibration exercise. In particular,
different approaches aiming at harmonized reference setting are tested. In this regard
the question is raised, whether good status can be defined without reference to
undisturbed conditions.
The four chapters of this dissertation cover a total of 26 national methods for the
ecological quality assessment of rivers using benthic invertebrates (15 methods),
macrophytes (9 methods) and benthic diatoms (2 methods). In the various analyses
more than 1,900 biological samples or surveys taken at rivers in 17 European countries
are processed. The work includes data of three stream types common to Member
States in Central and Western Europe, and four common types located in Eastern
Europe.
Each chapter comprises an individual case study focussing on specific quality elements
or distinct geographical regions. The basic approach throughout the thesis is to
compare the assessment methods using international datasets that cover river sites
impacted by different levels of anthropogenic pressure. This allows discrepancies to be
identified in the national quality class boundary settings that define good status, i.e. the
high-good and good-moderate boundaries. Following ECOSTAT (2004a) two options of
intercalibration are examined in this thesis: direct comparison of assessment methods
and indirect comparison of assessment methods using common metrics (Buffagni et
al., 2005).
The case studies provide a broad and coherent picture of the questions of
intercalibration. The contents of the four chapters are interdependent; in the first two
studies elementary intercalibration approaches are investigated on which the latter two
chapters are based. In Chapter 1 the direct comparison of invertebrate-based methods
is explored. By means of correlation analyses various biological indices are matched
for eight countries sharing two common stream types. The outcomes reveal strong
relationships between methods, but deviating definitions of good ecological quality.
Supportive environmental data is used to illustrate the level of anthropogenic pressure
associated with the respective good-moderate boundary of each national method.
13
Preface
The following two chapters deliver fundamental insights into the intercalibration of
assessment methods for river macrophytes. In search of the most suitable way for
comparing national classifications both intercalibration options are studied in Chapter 2.
The results show that national macrophyte methods are conceptually different, making
intercalibration even more challenging. In particular, divergences in the detection of
pressures (nutrient enrichment versus unspecific stresses) and the definition of the
natural reference state become evident. In view of these difficulties Chapter 3 identifies
the similarities of national methods to establish common grounds in macrophyte
intercalibration. Sites classified in either high or bad status by the majority of national
methods allow for a generic description of macrophyte communities under undisturbed
and degraded conditions. Furthermore, method comparison is enabled by delineating
indicator taxa that are used in a common metric for macrophytes.
The work of Chapter 4 includes the comparison of ecological classifications for five
Eastern European countries. Common metrics are applied in the intercalibration of
national methods using benthic diatoms and invertebrates. The availability of data from
undisturbed reference sites, indispensable for the intercalibration approach described
by Kelly et al. (2008) and Owen et al. (2010), is generally scarce for most of the stream
types dealt with in this chapter. Therefore, an alternative approach based on sites
impacted by similar levels of disturbance is employed. The biological benchmarks
derived from these sites set transnational reference points for the harmonization of
national quality classifications. For Austria and the Slovak Republic the outcomes of
this study have led to legally binding requirements that are stipulated in a Commission
Decision on quality class boundaries (European Commission, 2008).
The contents of this thesis contribute to the early outcomes of the ongoing
intercalibration process, that now involves an increasing number of scientists all over
Europe. The work at hand represents an essential contribution to the process of
successfully completing intercalibration. Moreover, this dissertation can be seen in
support of implementing a moral standard by scientific means: the definition of the right
conduct towards the environment.
14
Chapter 1: Direct comparison of assessment methods using benthic macroinvertebrates
15
1 Direct comparison of assessment methods using benthic macroinvertebrates: a contribution to the EU Water Framework Directive intercalibration exercise
1.1 Introduction
In the individual European countries the practice of evaluating ecological river quality is
very different (Metcalfe-Smith, 1994; Knoben et al., 1995; Birk & Hering, 2002).
Although river monitoring programmes in most countries are based on the benthic
macroinvertebrate community, design and performance of individual methods to
assess rivers with this organism group vary significantly. On the one hand this is due to
different traditions in stream assessment. While in many Central and Eastern European
countries modifications of the Saprobic System have been applied for decades as
standard methods (Birk & Schmedtje, 2005, see also Chapter 4), other countries rely
on the Biological Monitoring Working Party score (BMWP, 1978), which has been
adjusted for the use in various countries (Armitage et al., 1983; Just et al., 1998; Alba-
Tercedor & Pujante, 2000; Kownacki et al., 2004). On the other hand the EU Water
Framework Directive had a great effect on European freshwater management, since it
outlines an innovative concept of bioassessment: Not the impact of single pressures on
individual biotic groups but the deviation of the community from undisturbed conditions
is decisive for ecological status classification. In many EU Member States efforts are
being made to adapt the national programmes to these new requirements; however,
different approaches are being used, since in some countries a single stressor (e.g.
organic pollution) is overwhelming, while in other regions different stressors are of
equal importance and simultaneously affect river inhabiting communities.
To overcome the difficulties in comparing the various national assessment methods the
Directive outlines an intercalibration procedure of the methods’ outputs. Member States
are enabled to establish or to maintain their own methods; a definition of high, good or
moderate biological quality is provided centrally through the intercalibration exercise.
The aim of the intercalibration exercise is to identify and to resolve significant
inconsistencies between the quality class boundaries established by Member States
and indicated by the normative definitions of the Directive (ECOSTAT, 2004a).
The first efforts to compare different national assessment methods in Europe go back
to 1975. Three intercalibration campaigns organised by the Commission of the
Chapter 1: Direct comparison of assessment methods using benthic macroinvertebrates
European Communities included comparisons of field sampling, sample treatment and
quality assessment applied in Germany, Italy and United Kingdom (Tittizer, 1976;
Woodiwiss, 1978; Ghetti & Bonazzi, 1980). These early studies established strong
correlations between the individual assessment methods and compared the methods
directly. This approach towards intercalibration was then followed by various authors
both to demonstrate the relationship of methods and to point out discrepancies
between national quality classifications (Ghetti & Bonazzi, 1977; Rico et al., 1992;
Friedrich et al., 1995; Biggs et al., 1996; Morpurgo, 1996; Stubauer & Moog, 2000). In
their preparatory study for the Water Framework Directive Nixon et al. (1996) explicitly
recommended direct comparison to be used for the intercalibration of assessment
methods.
However, the official intercalibration exercise for the Water Framework Directive has
adopted an alternative approach due to the lack of comparable base data: indirect
comparison via Intercalibration Common Metrics, thus, generating a “common”
multimetric assessment procedure, which is more or less applicable in most of Europe,
and comparing national assessment methods against this common method (Buffagni et
al., 2006).
In this chapter I
(1) evaluate the principal suitability of directly comparing assessment methods for
intercalibration procedures;
(2) test a variety of different regression techniques to refine the practical application of
direct comparison for intercalibration purposes;
(3) directly compare assessment methods frequently applied for two broadly defined
European river types and suggest steps for harmonizing class boundaries.
1.2 Methods
1.2.1 Overview
This study was based on a two-step analysis: First, different assessment methods,
which are presently being used in national water management, were calculated with
the same taxa lists. The results of the individual assessment methods were then
directly compared by regression analysis.
16
Chapter 1: Direct comparison of assessment methods using benthic macroinvertebrates
All data used in this study resulted from the AQEM project (Hering et al., 2004) and the
STAR project (Furse et al., 2006). Only data on invertebrate samples restricted to two
broadly defined stream types were used. With the data from each stream type up to 10
national assessment systems were calculated, which were first normalized by
calculating “Ecological Quality Ratios” (i.e. transferring the results into a common scale
ranging from 0 to 1 where 1 equals the reference condition). These normalized
assessment results were fed into a regression analysis, to translate the index results of
country A into the index results of country B. Comparison of more than two methods
was enabled by including the index of country C and translating these results into the
index results of country B (“common scale”). In addition, the assessment results were
correlated to environmental gradients. In a second step, the class boundaries between
the individual quality classes, as applied by the national assessment systems, were
compared.
To test the impact of different regression techniques on the results, linear and nonlinear
techniques were compared.
1.2.2 Samples and sites
This study was based on benthic invertebrate data sampled in the EU projects AQEM
and STAR with standardised field and laboratory protocols (Furse et al., 2006). The
data were limited to two broadly defined stream type groups: small, siliceous mountain
streams and medium-sized lowland streams in Central and Western Europe. In the
official intercalibration exercise for the Water Framework Directive, these stream types
were named “small-sized, mid-altitude brooks of siliceous geology” (R-C3) and
“medium-sized, lowland streams of mixed geology” (R-C4) in Central Europe (Table 1).
294 samples taken at 125 sites located in four different countries in spring and summer
were analysed for the small mountain streams. The lowland stream type embraced a
total of 217 samples taken at 71 sites in four different countries in spring, summer and
autumn.
The ecological quality of each sampling site was pre-classified based on expert
judgement of the field researchers having sampled the streams and, if available,
additional knowledge derived from previous studies. Each site was assigned to one of
five quality classes (“high”, “good”, “moderate”, “poor”, “bad”) referring to the estimated
17
Chapter 1: Direct comparison of assessment methods using benthic macroinvertebrates
main stressor’s degree of impairment. For the AQEM sites, the pre-classification of
most sites was replaced by the post-classification after sampling due to additional
environmental parameters gained during the field work (physical-chemical and
hydromorphological variables).
Table 1: Overview of samples included in the analysis
Stream type Country Stream type Ecoregion no. Number of samples
Austria Small-sized shallow mountain streams 9 36
Small-sized shallow mountain streams 9, 10 40
Small-sized streams in the Central Sub-alpine Mountains 9 32 Czech Republic
Small-sized streams in the Carpathians 10 28
Small streams in lower mountainous areas of Central Europe
9 86 Germany
Small-sized Buntsandstein-streams 9 24
Small siliceous mountain streams
Slovak Republic Small-sizes siliceous mountains streams in the West Carpathians
10 48
Denmark Medium-sized deeper lowland streams 14 46
Germany Mid-sized sand bottom streams in the German lowlands
14 86
Medium-sized deeper lowland streams 14 14 Sweden
Medium-sized streams on calcareous soils 14 35
Medium-sized lowland streams
United Kingdom Medium-sized deeper lowland streams 18 36
1.2.3 National assessment methods and quality classifications
Altogether ten biological assessment indices were compared in this analysis (Table 2),
all of which are either in current usage in certain European countries or are about being
implemented into water management as standard techniques. Most represented biotic
index or score methods (Saprobic Index, Biological Monitoring Working Party Score,
Average Score Per Taxon, Danish Stream Fauna Index). All indices were part of the
respective national method planned for biological monitoring in the context of the Water
Framework Directive. With the exception of DSFI and ASPT, applied in Sweden,
calculation of index values was based on a nationally adjusted indicator species list.
For the indices applied in Austria, the Czech Republic, Germany and Denmark, stream
type specific reference values existed; these described the value of an index to be
expected under “undisturbed conditions”. The system used in the United Kingdom
predicted site specific reference values, Sweden defined reference conditions for
18
Chapter 1: Direct comparison of assessment methods using benthic macroinvertebrates
broad-scale natural geographical regions but in Poland and the Slovak Republic
reference values have not yet been established. All indices distinguished between five
classes of biological quality. The British and Swedish methods and the German
multimetric index defined class boundary values as Ecological Quality Ratios. The
Polish BMWP and the Saprobic Systems used quality classes given as absolute index
values. The Austrian, Czech and German quality bands were stream type specific. An
overview of nationally defined reference conditions and class boundaries is given in
Table 3.
Table 2: Overview of national assessment methods (BI - Biotic Index, MI – Multimetric Index)
Stream type Country Assessment index Category Abundance Reference
Austria SI (AT) – Austrian Saprobic Index BI Y Moog et al. (1999)
Czech Republic SI (CZ) – Czech Saprobic Index BI Y CSN 757716 (1998)
Germany SI (DE) – German Saprobic Index BI Y Friedrich & Herbst (2004)
Poland BMWP (PL) – Polish Biological Monitoring Working Party score BI N Kownacki et al.
(2004)
Slovak Republic SI (SK) – Slovak Saprobic Index BI Y STN 83 0532-1 to 8 (1978/79)
Small siliceous mountain streams
United Kingdom ASPT (UK) - Average Score Per Taxon BI N Armitage et al.
(1983)
Denmark DSFI (DK) – Danish Stream Fauna Index BI N Skriver et al.
(2000)
Germany
GD (DE) – Module “General Degradation” of the German Assessment System Macrozoobenthos
MI1 Y Böhmer et al. (2004)
ASPT (SE)- Average Score Per Taxon applied in Sweden BI N
Sweden DSFI (SE) – Danish Stream Fauna Index applied in Sweden
BI N
Swedish Environmental Protection Agency (2000)
Medium-sized lowland streams
United Kingdom ASPT (UK) - Average Score Per Taxon
BI N Armitage et al. (1983)
1.2.4 Data preparation
National assessment methods were calculated to the taxa lists of each sample.
Absolute index values were converted into Ecological Quality Ratios (EQR) by dividing
1 Includes the following single metrics: “relative abundance of ETP taxa”, “German Fauna Index Type 15”,
“number of Trichoptera taxa”, “Shannon-Wiener diversity”, “share of rheobiontic taxa”, “share of shredders [%]”
19
Chapter 1: Direct comparison of assessment methods using benthic macroinvertebrates
the calculated (observed) value by the index specific reference value. Since, for the
Saprobic Indices, biological quality decreased with increasing index values these were
converted by the following equation:
observed SI value – reference SI value EQR SI = 1 -
maximum SI value – reference SI value
To validate the national reference values, an index specific reference value was
calculated as the 75th percentile of all samples taken at sites pre- or post-classified as
high quality status (excluding outliers). For the small mountain streams, sampling sites
located in Austria (6 samples), Czech Republic (14 samples), Germany (13 samples)
and Slovak Republic (1 sample) were used. For the lowland type sites from Denmark
(13 samples), Germany (26 samples), Sweden (2 samples) and United Kingdom
(9 samples) were the basis of this calculation.
Table 3: Original reference and class boundary values of the national assessment methods (abs – absolute value).
Small siliceous mountain streams
Index SI (AT) SI (CZ) SI (DE) BMWP (PL) SI (SK) ASPT (UK)
Reference (abs) ≤ 1.50 ≤ 1.20 ≤ 1.25 n.a. n.a. ≥ 6.622
High|good 1.50 1.20 1.40 100 1.79 1.00
Good|moderate 2.10 1.50 1.95 70 2.30 0.89
Moderate|poor 2.60 2.00 2.65 40 2.70 0.77
Poor|bad 3.10 2.70 3.35 10 3.20 0.66
Lit. source - Brabec et al. (2004) Rolauffs et al.
(2003) Kownacki et al.
(2004) STN 83 0532-1 to 8 (1978/79)
National Rivers Authority (1994)
Medium-sized lowland streams
Index DSFI (DK) GD (DE) BMWP (PL) ASPT (SE) DSFI (SE) ASPT (UK)
Reference (abs) 7 1 n.a. ≥ 4.7 ≥ 5 ≥ 6.382
High|good 7 0.80 100 0.90 0.90 1.00
Good|moderate 5 0.60 70 0.80 0.80 0.89
Moderate|poor 4 0.40 40 0.60 0.60 0.77
Poor|bad 3 0.20 10 0.30 0.30 0.66
Lit. source - Böhmer et al. (2004) Kownacki et al.
(2004)
Swedish Environmental
Protection Agency (2000)
Swedish Environmental
Protection Agency (2000)
National Rivers Authority (1994)
Conversion into the EQR scale resulted in values ranging from 0 to >1 since several
samples revealed biological index values representing higher quality than the
respective reference value. These values were not transformed into the value “1” in
2 Values were derived by RIVPACS predictions for the corresponding stream type group based on
averaged environmental parameter values and combined season information for the analysed samples.
20
Chapter 1: Direct comparison of assessment methods using benthic macroinvertebrates
order to improve the correlation and regression analysis by enlarging the quality
gradient.
1.2.5 Correlation and regression analysis
The magnitude of the relation between two assessment methods was specified by the
“coefficient of determination”. Beside linear regression, I applied nonlinear modelling
via automatic curve-fitting using the software TableCurve 2D (SYSTAT Software Inc.,
2002).
1.2.6 Comparison of quality class boundaries
In order to compare the national quality classes the boundary values of the different
assessment methods were transformed into a “common scale”. In this study two
common scales were used: (1) The national method showing the highest mean
correlation of all indices. (2) The “Integrative Multimetric Index for Intercalibration” (IMI-
IC), an artificial index designed here for the purpose of intercalibration. This index was
defined as the mean of all index values calculated for a sample. The transformation
was done based on the results of linear regression analyses, in which the predictor
variables were represented by the national indices and the response variables by the
“common scale”. Each boundary value transformed by regression was given including
its 95 percent confidence interval. Class boundaries showing overlapping ranges
(translated class boundary +/- confidence interval) were considered as being equal.
Based on environmental variables, abiotic gradients were generated for each stream
type and the pressure gradients best correlating to the methods analysed in this
intercalibration approach were identified. Indirect gradient analysis was aimed at the
identification and quantification of physical-chemical and hydromorphological gradients
that can be assigned to human impairment. Therefore, Principle Component Analysis
(PCA) was run separately on correlation matrices of physical-chemical, catchment land
use, hydromorphological and microhabitat variables of the mountain and lowland
dataset. A dimensionless value of abiotic pressure, including the 95 percent confidence
interval, was assigned to each national class boundary via regression analysis. These
pressure data were used to support class boundary comparisons.
21
Chapter 1: Direct comparison of assessment methods using benthic macroinvertebrates
1.3 Results
1.3.1 Definition of reference values
The 75th percentiles of reference values were specified in Table 4. Each reference was
based on a slightly different number of samples due to the elimination of outliers.
Except for the German indices and the assessment methods for which no reference
was nationally defined (Polish BMWP and Slovak SI), the 75th percentile, as calculated
in this study, generally represented higher biological quality than the minimum values
of the national reference.
Table 4: Reference values of national assessment methods derived by using the 75th percentile of index values calculated from samples taken at high status sites. For small mountain
streams the number of high status sites’ samples is individually specified in brackets. Values of lowland streams are based on 50 samples.
Small siliceous mountain streams
Index SI (AT) SI (CZ) SI (DE) BMWP (PL) SI (SK) ASPT (UK)
75th percentile 1.46 (32) 0.91 (34) 1.44 (33) 187 (33) 1.21 (30) 7.26 (33)
Medium-sized lowland streams
Index DSFI (DK) GD (DE) BMWP (PL) ASPT (SE) DSFI (SE) ASPT (UK)
75th percentile 7 0.67 150 6.57 7 6.57
1.3.2 Descriptive statistics of national indices calculated from the AQEM-STAR datasets
The overall mean of normalized index values (0 to 1) for the small mountain streams
amounted to 0.87, while the same statistic for medium-sized lowland streams was 0.77
(Table 5). The maximum values of all indices except DSFI exceeded 1.0. This was due
to the selection of the 75th percentile of AQEM-STAR high status sites as the reference
value. The values of the Polish BMWP and the German GD covered ranges of more
than 1.0, while the Austrian and German SI, and the British and Swedish ASPT
showed value ranges of less than 0.65.
1.3.3 Correlation and regression of national assessment methods
The correlation analysis revealed differences between assessment methods (Table 6).
The linear equations of the regression analysis of national methods against methods
representing a common scale (best correlating national index, IMI-IC) are displayed in
22
Chapter 1: Direct comparison of assessment methods using benthic macroinvertebrates
Table 7. Nonlinear equations are listed additionally if they provide higher coefficients of
determination.
Table 5: Descriptive statistics of national indices calculated from the AQEM-STAR datasets (normalized index values).
Small siliceous mountain streams (n = 294) Mean Minimum Maximum 25th percentile 75th percentile Range Quartile range
SI (AT) 0.902 0.526 1.112 0.833 0.972 0.585 0.138
SI (CZ) 0.853 0.374 1.112 0.761 0.963 0.739 0.202
SI (DE) 0.920 0.444 1.055 0.895 0.984 0.611 0.088
BMWP (PL) 0.768 0.102 1.273 0.636 0.936 1.171 0.299
SI (SK) 0.890 0.444 1.281 0.798 0.984 0.837 0.186
ASPT (UK) 0.908 0.448 1.077 0.869 0.988 0.629 0.119
Medium-sized lowland streams (n = 217) Mean Minimum Maximum 25th percentile 75th percentile Range Quartile range DSFI (DK) and DSFI (SE) 0.767 0.286 1.000 0.571 1.000 0.714 0.429
GD (DE) 0.709 0.090 1.149 0.552 0.896 1.060 0.343
BMWP (PL) 0.741 0.173 1.480 0.580 0.900 1.307 0.320 ASPT (SE) and ASPT (UK) 0.869 0.457 1.091 0.797 0.956 0.634 0.159
For small mountain streams coefficients of determination ranged from 0.20 (Slovak SI
and Polish BMWP) to 0.77 (Austrian SI and Slovak SI). Nonlinear regression gained
higher R2 values in 23 out of 36 relations. The mean difference in R2 values between
linear and nonlinear regressions was 0.04. The maximum difference in R2 values of
0.12 was between linear and nonlinear equations for the relationship between SI (SK)
and ASPT (UK). German SI had the highest average correlation to the other
assessment methods (R2 = 0.67). The IMI-IC for this stream type was characterised by
coefficients of determination ranging from 0.62 (Slovak SI) to 0.87 (German SI). In
Figure 1 regression lines of BMWP (PL) against SI (DE) were exemplarily plotted for
linear and nonlinear regression. R2 values for regressions of methods for the lowland
streams varied between 0.41 (German GD and Polish BMWP) and 0.67 (British and
Swedish ASPT, and Danish and Swedish DSFI). In 6 out of 16 correlations, nonlinear
regression provided a higher proportion of the variance explained. Mean difference of
the linear and nonlinear coefficients of determination was R2 = 0.02 and the maximum
difference was R2 = 0.06 (Polish BMWP and British ASPT). DSFI showed the highest
mean correlation for the lowland samples (R2 = 0.60). The IMI-IC had coefficients of
determination ranging from 0.73 (Polish BMWP) to 0.90 (Danish and Swedish DSFI).
All correlations were significant at p < 0.05. Since none of the differences between the
23
Chapter 1: Direct comparison of assessment methods using benthic macroinvertebrates
linear and nonlinear coefficients of determination were significant, I assumed linear
relationships between indices in the following analyses.
0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4
BMWP (PL)
0.2
0.4
0.6
0.8
1.0
1.2
1.4
SI (
DE
)
Figure 1: Regression of BMWP (PL) against SI (DE). Both linear (R2 = 0.53, dashed) and nonlinear (R2 = 0.63) regression lines are plotted.
1.3.4 Correlation to environmental gradients (PCA)
Index values of the small mountain streams showed the strongest relationship with the
PCA gradient reflecting nutrient enrichment and organic pollution. Determination
coefficients of this gradient and the assessment methods varied from 0.19 (Slovak SI)
to 0.53 (British ASPT). Index values of the lowland streams showed highest
correlations with the main hydromorphological gradient that comprised physical
features of the river channel, its banks and immediate vicinity, including information on
the degree of impairment. The coefficients of determination ranged between 0.12
(Polish BMWP) and 0.35 (German GD).
24
Chapter 1: Direct comparison of assessment methods using benthic macroinvertebrates
1.3.5 Comparison of national quality classes
The comparison of biological quality classes was based on the transformation of
boundary values of the assessment methods into a common scale. This allowed for a
direct juxtaposition of class boundaries in Table 8.
Small-sized siliceous mountain streams
The common scales used in the comparison procedure for the mountain streams were
SI (DE) and IMI-ICR-C3 (multimetric index composed of all national assessment
methods). In SI (DE) scale, the high-good boundaries of SI (AT) and ASPT (UK) were
similar considering the 95 percent confidence interval. ASPT (UK) and SI (CZ) showed
overlapping good-moderate boundary intervals and thus shared equal class
boundaries. The same applied for the group of indices SI (AT), SI (DE), BMWP (PL)
and SI (SK). Based on IMI-ICR-C3 the high-good boundaries of SI (AT) and ASPT (UK)
shared common intervals. For the good-moderate boundary the comparison showed
similar values for SI (AT), BMWP (PL) and SI (SK).
The pollution/eutrophication gradient showed similar pressure between high-good
boundaries of SI (AT), SI (CZ), SI (DE), ASPT (UK), and BMWP (PL) and SI (SK). For
the good-moderate boundary corresponding levels of chemical impairment were
between SI (AT) and SI (DE), SI (SK) and BMWP (PL), and SI (CZ) and ASPT (UK).
The average confidence interval amounted to 0.025 units.
Medium-sized, lowland, mixed geology
The DSFI and IMI-ICR-C4 (multimetric index composed of all national assessment
methods) were used as common scales for the boundary comparisons of the lowland
stream type. Using DSFI as the common scale, none of the national indices showed
similar high-good class boundaries but the good-moderate boundaries of DSFI (SE)
and ASPT (UK) were corresponding. The average confidence interval amounted to
0.017 DSFI units.
25
Chapter 1: Direct comparison of assessment methods using benthic macroinvertebrates
26
Table 6: Coefficients of determination based on linear and nonlinear regression (p < 0.05) – (IMI-IC: Integrative Multimetric Index for Intercalibration (see text for explanation); PE1: pollution/eutrophication gradient; HY1: hydromorphological gradient)
Small siliceous mountain streams (n = 294) Index SI (AT) SI (CZ) SI (DE) BMWP (PL) SI (SK) ASPT (UK)
linear nonl. linear nonl. linear Nonl. linear nonl. linear nonl. linear nonl.
SI (AT) 1.00 - 0.62 - 0.70 0.74 0.36 0.39 0.73 0.77 0.45 0.46
SI (CZ) 0.62 - 1.00 - 0.62 0.64 0.31 0.35 0.55 - 0.38 -
SI (DE) 0.70 0.73 0.62 0.70 1.00 - 0.53 0.63 0.48 0.56 0.69 0.73
BMWP (PL) 0.36 0.37 0.31 0.34 0.53 - 1.00 - 0.20 0.23 0.69 0.70
SI (SK) 0.73 - 0.55 - 0.48 0.51 0.20 0.21 1.00 - 0.24 0.26
ASPT (UK) 0.45 0.50 0.37 0.45 0.69 0.70 0.69 0.75 0.24 0.36 1.00 - IMI-ICR-C3 0.79 0.80 0.72 0.74 0.86 0.87 0.72 0.75 0.62 0.66 0.75 -
PE1 0.31 0.33 0.23 0.27 0.46 - 0.37 0.38 0.19 0.23 0.53 -
Medium-sized lowland streams (n = 217)
Index DSFI (DK) and DSFI (SE) GD (DE) BMWP (PL) ASPT (SE) and
ASPT (UK) linear nonl. linear nonl. linear nonl. linear nonl. DSFI (DK) and DSFI (SE) 1.00 - 0.61 - 0.53 0.54 0.65 -
GD (DE) 0.61 - 1.00 - 0.41 0.46 0.49 -
BMWP (PL) 0.53 0.54 0.41 - 1.00 - 0.51 - ASPT (SE) and ASPT (UK) 0.65 0.67 0.49 0.50 0.51 0.57 1.00 - IMI-ICR-C4 0.90 - 0.76 - 0.73 0.75 0.80 -
HY1 0.23 - 0.35 - 0.12 0.13 0.24 0.26
Chapter 1: Direct comparison of assessment methods using benthic macroinvertebrates
Table 7: Coefficients of linear regression equations (a - slope, b - intercept) for the common scales and the abiotic gradients (IMI-IC: Integrative Multimetric Index for Intercalibration (see text for explanation); PE1: pollution/eutrophication gradient; HY1: hydromorphological gradient)
Small siliceous mountain streams Index SI (AT) SI (CZ) SI (DE) BMWP (PL) SI (SK) ASPT (UK)
Parameter a b a b a b a b a b a b
SI (DE) 0.784 0.212 0.562 0.440 1.000 0 0.319 0.675 0.511 0.465 0.687 0.296
IMI-ICR-C3 0.992 -0.021 0.717 0.261 1.100 -0.138 0.441 0.535 0.688 0.261 0.850 0.102
PE1 -0.845 1.000 -0.567 0.720 -1.089 1.236 -0.450 0.577 -0.542 0.721 -0.976 1.120
Medium-sized lowland streams Index DSFI (DK) and DSFI (SE) GD (DE) BMWP (PL) ASPT (SE) and ASPT (UK)
Parameter a b a b a b a b
DSFI 1.000 0.000 0.579 0.356 0.344 0.570 1.349 -0.405
IMI-ICR-C4 0.825 0.154 0.566 0.386 0.357 0.580 1.301 -0.343
HY1 -0.627 0.934 -0.583 0.857 -0.360 0.720 -1.078 1.396
27
Chapter 1: Direct comparison of assessment methods using benthic macroinvertebrates
Table 8: EQR values of the high-good (H|G) and good-moderate (G|M) quality class boundaries transferred into “common scale”. In addition, the values of the abiotic gradients (PE1, HY1) corresponding to the national class boundaries are displayed. For each value derived by regression the 95 percent confidence interval is specified (IMI-IC: Integrative Multimetric Index for Intercalibration (see text for explanation); PE1:
pollution/eutrophication gradient; HY1: hydromorphological gradient)
Small siliceous mountain streams SI (AT) SI (CZ) SI (DE) BMWP (PL) SI (SK) ASPT (UK)
Cla
ss
boun
dary
Com
mon
sca
le
Boun
dary
va
lue
95%
co
nfid.
Boun
dary
va
lue
95%
co
nfid.
Boun
dary
va
lue
95%
co
nfid.
Boun
dary
va
lue
95%
co
nfid.
Boun
dary
va
lue
95%
co
nfid.
Boun
dary
va
lue
95%
co
nfid.
SI (DE) 0.984 0.008 0.949 0.008 1.016 - 0.846 0.011 0.870 0.010 0.983 0.008
IMI-ICR-C3 0.955 0.008 0.911 0.008 0.979 0.008 0.771 0.010 0.806 0.011 0.952 0.009 H|G
PE1 0.169 0.023 0.206 0.019 0.130 0.023 0.336 0.022 0.291 0.023 0.144 0.019
SI (DE) 0.799 0.012 0.895 0.007 0.801 - 0.794 0.016 0.776 0.020 0.907 0.006
IMI-ICR-C3 0.721 0.012 0.842 0.008 0.743 0.009 0.700 0.015 0.680 0.021 0.858 0.007 G|M
PE1 0.368 0.032 0.262 0.019 0.364 0.025 0.409 0.032 0.391 0.045 0.251 0.014
Medium-sized lowland streams DSFI (DK) GD (DE) BMWP (PL) ASPT (SE) DSFI (SE) ASPT (UK)
Cla
ss
boun
dary
Com
mon
sca
le
Boun
dary
va
lue
95%
conf
id.
Boun
dary
va
lue
95%
conf
id.
Boun
dary
va
lue
95%
conf
id.
Boun
dary
va
lue
95%
conf
id.
Boun
dary
va
lue
95%
conf
id.
Boun
dary
va
lue
95%
conf
id.
DSFI 1.000 - 1.048 0.012 0.724 0.018 0.809 0.016 0.900 - 0.944 0.025
IMI-ICR-C4 0.979 0.012 1.061 0.008 0.744 0.012 0.827 0.011 0.897 0.009 0.958 0.017 H|G HY1 0.307 0.054 0.162 0.021 0.480 0.036 0.426 0.035 0.370 0.042 0.318 0.054
DSFI 0.714 - 0.875 0.016 0.610 0.016 0.674 0.019 0.800 - 0.795 0.016
IMI-ICR-C4 0.744 0.008 0.892 0.011 0.628 0.011 0.697 0.012 0.814 0.007 0.814 0.010 G|M HY1 0.486 0.035 0.335 0.030 0.552 0.034 0.534 0.041 0.432 0.035 0.437 0.034
28
Chapter 1: Direct comparison of assessment methods using benthic macroinvertebrates
Table 9: Comparison of the saprobic indicator taxa lists of Austria, Czech Republic, Germany and Slovak Republic: Share of common taxa and coefficients of determination derived from correlation analysis of indicator values and indicator weights.
SI (AT) SI (CZ) SI (DE) SI (SK)
Share of common
taxa
Indicator value
Indicator weight
Share of common
taxa
Indicator value
Indicator weight
Share of common
taxa
Indicator value
Indicator weight
Share of common
taxa
Indicator value
Indicator weight
SI (AT) - 1.00 1.00 56 % 0.64 0.14 72 % 0.74 0.04 77 % 0.88 0.53
SI (CZ) 36 % 0.64 0.14 - 1.00 1.00 54 % 0.74 0.14 53 % 0.73 0.31
SI (DE) 35 % 0.74 0.04 41 % 0.74 0.14 - 1.00 1.00 41 % 0.73 0.04
SI (SK) 45 % 0.88 0.53 48 % 0.73 0.31 49 % 0.73 0.04 - 1.00 1.00
29
Chapter 1: Direct comparison of assessment methods using benthic macroinvertebrates
30
In the IMI-ICR-C4 scale, the high-good boundaries of DSFI (DK) and ASPT (UK) had
similar values and the good-moderate boundaries of DSFI (SE) and ASPT (UK)
corresponded closely. Confidence intervals showed an average value of 0.011 units.
Boundary comparisons using the hydromorphological gradient were difficult because
the large confidence intervals (0.038 units in average) resulted in overlapping boundary
ranges. Both good quality boundaries of GD (DE) showed the lowest level of pressure.
For the good-moderate boundary, levels of pressure were similar between DSFI (DK),
DSFI (SE) and ASPT (UK), and between BMWP (PL) and ASPT (SE).
1.4 Discussion
1.4.1 Role of reference conditions in the intercalibration exercise
Within the intercalibration exercise, class boundaries of national assessment methods
need to be defined as Ecological Quality Ratios. The position of each boundary on this
relative scale is dependent on (1) the definition of reference conditions and (2) the
procedure of setting class boundaries. If the former is not properly dealt with in the
intercalibration process, the different nationally defined reference values may strongly
impact upon comparability.
In this chapter I have defined a common reference, which is based on sites in several
countries. As a result of this common reference, it was possible to include several
methods in the comparison, even if countries have not yet defined reference values for
a specific method. A further advantage of common references is that differences in
national approaches to define references are avoided. On the other hand, common
references are in danger of not adequately accounting for the differences between the
more specific national streams types.
More importantly, countries have applied different procedures to define reference
values and quality classification schemes. While this study is restricted to the analysis
of national class boundary settings, it must be an objective of the official intercalibration
exercise to overcome differences in the references too.
1.4.2 Relations between assessment methods
In this study, the calculation of national assessment metric values is based on taxa lists
derived by application of the standardised STAR-AQEM field and laboratory protocol.
Chapter 1: Direct comparison of assessment methods using benthic macroinvertebrates
Thus, the correlation analyses of index values mainly reveal the numerical relation
between these indices and is less biased by differences in field and laboratory
procedures. The character of these relations depends on the architecture of the
individual indices, e.g. number and indicative value of taxa included in the evaluation,
type of abundance information used and the assessment formula. The effect of
different national sampling methods on the comparability of taxa lists and metric results
as a major constraint of intercalibration is investigated by Friberg et al. (2006). Buffagni
et al. (2006) present a practical approach enabling the use, in intercalibration, of
datasets derived by the national monitoring programmes.
An additional factor, impacting on the relationships, is the dataset itself, in particular the
number of samples, the biogeographical gradient, the types of pressures influencing
sampling sites and the range of degradation covered. The different ranges of index
values (cf. Table 5) indicate a larger degradation gradient being covered by the lowland
dataset. This is, in particular, obvious from the Polish BMWP and British ASPT values,
which have been calculated for both datasets.
For the mountain stream data, relationships are strongest between the values of the
different Saprobic Indices of Austria, Czech Republic, Germany and Slovak Republic
and between the score methods applied in Poland and the United Kingdom. In general,
the strength of correlations between the different Saprobic Indices results from
similarities in indicator taxa and their indication values (Table 9). For instance, the
Austrian and Slovak Saprobic Indices (R2 > 0.73) share the largest number of indicator
taxa and are most closely related concerning indicator taxa value and weight. Schmidt-
Kloiber et al. (2006) provide a comprehensive analysis of saprobic indicator taxa
applied in Europe.
For the lowland stream dataset, BMWP (PL) and ASPT (UK) correlate less strongly
(R2 < 0.60), which can be explained by the different taxonomic composition of the
lowland dataset compared to that of the mountain streams. The two indices have 66
indicator taxa in common, amounting to a share of 73 percent (Polish BMWP) and
80 percent (British ASPT), respectively. BMWP indicator values of the common taxa in
the Polish and British systems are correlated with R2 = 0.73.
31
Chapter 1: Direct comparison of assessment methods using benthic macroinvertebrates
Method comparisons of earlier studies show similar results. Based on 232 samples
from various lowland and mountain stream types in Germany, Friedrich et al. (1995)
found correlations of R2 = 0.71 between ASPT (UK) and a previous version of the
German Saprobic Index. The weak relation of ASPT and the Austrian Saprobic Index
has already been demonstrated by Stubauer & Moog (2000), who used a large dataset
covering all Austrian stream types (n = 588; R2 = 0.52). Analyses of Birk & Rolauffs
(2004) revealed strong correlations between the Austrian and German Saprobic
Indices (n = 262; R2 = 0.75).
Several indices revealed higher coefficients of determination when applying a nonlinear
fit, in particular if BMWP (PL) was involved. This index combines the parameters taxon
richness and sensitivity into a single value which may cause the observed relationship.
Also, due to the large range of values covered by the method, the nonlinearity of the
relationships became evident (cf. Figure 1). Nevertheless, these difference of the
coefficients of determination are not significant. Therefore, the simple model of linear
relationship between indices is most appropriate in this example of direct comparison.
1.4.3 Comparison of class boundary values
While earlier intercalibration studies focussed on the comparison of quality class bands
(Ghetti & Bonazzi, 1977; Friedrich et al., 1995; Morpurgo, 1996), the Water Framework
Directive specifically requires the comparability of the high-good and good-moderate
quality class boundaries. Thus, the intercalibration exercise is focussed on the range
medium to high biological quality. The original procedure outlined in the Directive is
restricted to the use of just a few intercalibration sites, selected because they represent
the boundary status between quality classes. However, this approach seems not to be
feasible, since sites known to be on class boundaries cannot be selected prior to the
intercalibration is completed and those boundaries are defined. Furthermore, the
uncertainty of intercalibration results is high if the analysis is based on insufficient data.
Therefore, the primary step, in comparing national class boundary values and best
identifying the type and magnitude of the relationship between national assessment
methods, should be based on a large number of samples covering the entire quality
gradient. In a further step, regression analysis should be used to transform boundary
values into other assessment scales. By applying an acceptable level of uncertainty
32
Chapter 1: Direct comparison of assessment methods using benthic macroinvertebrates
(e.g. confidence interval of 95 percent derived from regression analysis), ranges of
index values can be compared.
The comparison of assessment methods has revealed discrepancies between national
classification schemes of more than 25 percent in particular cases (e.g. high-good
boundary of German SI and Polish BMWP translated in German SI scale). The extent
of differences between class boundaries is largely dependent on the common scale
used for comparison. While class boundaries clearly differ if compared through the
German Saprobic Index scale, no differences occur between the same boundaries if
compared through a multimetric index. Each method used as a common scale is
somewhat related to other assessment methods as expressed by the correlation
coefficient and the regression equation.
Based on these findings I recommend using the intercalibration approach described in
this chapter only for comparison of methods addressing similar components of the
biocoenosis, e.g. for methods that are closely related such as ASPT, BMWP and the
Saprobic Indices, or methods that are fully compliant with the requirements of the
Water Framework Directive (i.e. methods evaluating taxonomic composition and
abundance, ratio of disturbance sensitive to insensitive taxa and diversity of the
macroinvertebrate community). This principle makes sure that “like with like”
comparisons are applied in intercalibration and minimises errors in the comparison
analysis due to the selection of inappropriate common scales. Furthermore, the relation
between assessment methods needs to be carefully evaluated. Nonlinear correlations
yielding significantly better fit and smaller confidence intervals are to be favoured over
weaker linear relations.
1.4.4 When shall boundaries be considered as different?
Intercalibration encompasses two steps: Firstly, national quality boundaries are
compared. If this analysis discovers major differences in classification schemes, they
need to be harmonized in a second step. For the first step, I have described a possible
procedure to translate boundary values into a common scale, which determines
whether or not boundary values are corresponding. According to my results only a few
class boundaries are similar, which thus requires the remaining boundaries to be
harmonized.
33
Chapter 1: Direct comparison of assessment methods using benthic macroinvertebrates
The use of abiotic pressure data in intercalibration allows for additional interpretation of
results. Sandin & Hering (2004) applied organic pollution gradients to set
intercalibration class boundaries defining a standard level of pollution. I particularly
propose to use pressure information for the process of boundary comparison. Figure 2
displays the relative position of the national good-moderate boundaries, including
confidence intervals translated into a common biotic scale and an abiotic pressure
scale (pollution/eutrophication gradient). Comparisons based on the interpretation of
biotic data indicate that four out of six class boundaries are deviating (cf. Table 8),
while the consideration of pressure data (Figure 2) reveals only two groups of
boundaries with overlapping pressure intervals. Thus, harmonization is only needed
between the two groups of boundaries.
AS
PT (U
K)
SI (C
Z)
SI (D
E)
SI (A
T)
BM
WP
(PL)
SI (S
K)
AS
PT (U
K)
SI (C
Z)
SI (D
E)
SI (A
T)
BM
WP
(PL)
SI (S
K)
IMI-IC PE1
Figure 2: Relative comparison of good-moderate class boundary values (incl. 95 percent
confidence intervals) using IMI-ICR-C3 and corresponding chemical pressure values of the small siliceous mountain streams. Based on the results of the pressure data analysis two groups of similar boundaries are highlighted by dashed circles.
1.5 Conclusions
Intercalibration represents a crucial step towards the implementation of a pan-
European water quality standard. Besides scientific issues, which I partly addressed in
this chapter, it holds a major social challenge. Although assessment methods are in
34
Chapter 1: Direct comparison of assessment methods using benthic macroinvertebrates
general scientifically sound instruments, the element of quality classification is a
concession to the practical requirements of decision making in water policy. According
to the Water Framework Directive the quality assigned to a site can decide on
restoration efforts to be spent or saved. Therefore, intercalibration is of political interest
since the definition of quality boundaries sets the environmental standard to be
achieved. Furthermore, intercalibration holds an ethical component: By selecting
certain quality criteria we agree on a level of anthropogenic degradation acceptable for
our freshwater systems. Although beyond its scope science needs to consider all these
aspects in the preparation of reasonable and tenable results.
35
Chapter 2: Intercalibration of assessment methods for macrophytes in lowland streams
36
2 Intercalibration of assessment methods for macrophytes in lowland streams: direct comparison and analysis of common metrics
2.1 Introduction
According to the EU Water Framework Directive (WFD; European Commission, 2000)
European surface waters must achieve good ecological quality by the year 2015.
Responsibility for the quality assessment lies with the individual Member States, which
have developed or modified assessment methods at the national level. To ensure the
comparability of the national methods, an intercalibration exercise is stipulated by the
Directive, in which quality class boundaries are checked for comparability and
consistency with normative requirements.
Although benthic macroinvertebrates are presently most commonly applied for the
quality assessment of rivers (Birk & Hering, 2002), macrophytes are also surveyed in
some countries to monitor the effects of anthropogenic pressures, especially
eutrophication (Kelly & Whitton, 1998; Birk & Schmedtje, 2005). Macrophytes were first
used in water quality assessment in relation to various modifications of the saprobic
system. Several indicator catalogues (e.g. Sládeček, 1973) included single macrophyte
species to evaluate the degree of organic pollution. More generally, the monitoring of
macrophyte communities was confined to the description of the vegetation without
inferring water quality (e.g. Holmes & Whitton, 1975; Janauer et al., 2003). With the
increasing awareness of the effects of nutrient enrichment the community assessment
of phototrophs gained in importance. The Mean Trophic Rank (MTR, Holmes et al.,
1999), for instance, focuses on the impact of nutrient enrichment only, since it was
elaborated and tested specifically for the application of the EU Urban Waste Water
Treatment Directive (Council of the European Communities, 1991). The Water
Framework Directive recently led to the development of national methods aimed at
assessment of ecological quality of the aquatic flora (e.g. Molen et al., 2004; Leyssen
et al., 2005; Meilinger et al., 2005). These methods differ in design and performance
from macroinvertebrate based systems and, thus, require a separate intercalibration
process.
The intercalibration procedure as outlined in the Directive comprises the comparison of
intercalibration sites whose individual biological quality, in the opinion of the Member
Chapter 2: Intercalibration of assessment methods for macrophytes in lowland streams
States, represents the boundary between quality classes. Recent studies on
intercalibration of macroinvertebrate methods are based on data representing a broad
quality gradient, and class boundaries are compared via correlation and regression
analysis. While in Chapter 1 of this thesis the national methods are directly compared
by the help of a “common scale” (method best correlating with all other methods),
Buffagni et al. (2006) use “common metrics” as a general scale. Common metrics are
defined as biological metrics widely applicable within a geographical region, which can
be used to derive comparable information among different countries and stream types
(Buffagni et al., 2005).
In this chapter I apply the two above outlined approaches of boundary comparison to
macrophyte data from lowland rivers covering a broad spectrum of anthropogenic
disturbance from reference to heavily impacted sites. Furthermore, I test both
techniques for their applicability in the intercalibration of four assessment methods for
macrophytes.
2.2 Methods
2.2.1 Samples and sites
This study is based on river macrophyte survey data collected at medium-sized lowland
streams in six countries in the framework of the EU project STAR (Furse et al., 2006).
In the official intercalibration exercise for the Water Framework Directive, this stream
type is named “medium-sized, lowland streams of mixed geology” (R-C4) in Central
Europe (ECOSTAT, 2004b). Data used here were limited to 108 sites at which
macrophytes covered at least 1 percent of the total channel area investigated (Table
10).
Table 10: Overview of the sites surveyed at medium-sized lowland streams.
Country Number of surveys Denmark 11 Germany 11 Latvia 36 Poland 24 Sweden 20 United Kingdom 6
Macrophytes were sampled using a single survey in late summer or early autumn. A
100 m stream length was surveyed in each stream by wading in a zigzag manner
37
Chapter 2: Intercalibration of assessment methods for macrophytes in lowland streams
across the channel. Macrophytes of non-wadable sites were observed by boat or by
walking along the banks. All macrophytes species were recorded as well as the percent
cover of the overall macrophyte growth. Species were normally identified in the field,
but if identification was uncertain a representative sample was collected for later
identification. In addition, physico-chemical data were sampled. Table 11 lists statistical
descriptors for the sampling site’s trophic status.
Table 11: Range of trophic status covered by the dataset (n=108): descriptive statistics of the chemical parameters nitrate and total phosphorus
Min 25th Median 75th Max Nitrate (mg l-1) 0.03 0.25 1.50 2.00 12.10 Total phosphorus (mg l-1) 0.01 0.09 0.21 0.28 15.40
2.2.2 National assessment methods and quality classifications
Four methods to assess the quality of streams, which are being used in France,
Germany, the Netherlands and the United Kingdom were compared (Table 12). All
methods are based on species-level data and integrate specific indicator values and
abundance information. Except for the German Reference Index, abundance is
specified in classes of relative plant coverage. Abundance data used by the German
index is an estimation of the three-dimensional structure of the instream vegetation
(Kohler, 1978). Table 13 compares the different macrophyte abundance schemes.
While the French and British methods were used alone, the German and Dutch indices
are part of generic methods to assess the “aquatic flora”, which is defined as including
macrophytes and phytobenthos.
Table 12: Overview of macrophyte assessment methods
Country Assessment method Reference
France IBMR (FR) – Indice Biologique Macrophytique en Rivière NF T90-395 (2003)
Germany RI (DE) – Reference Index Schaumburg et al. (2004)
The Netherlands DMS (NL) – Dutch Macrophyte Score (“Soortensamenstelling macrofyten”) Molen et al. (2004)
United Kingdom MTR (UK) – Mean Trophic Rank Holmes et al. (1999)
The Dutch and German methods aim at assessing the degree of deviation from the
reference state and are, thus, based on stream type specific reference conditions. It is
therefore necessary to classify the streams sampled here into specific stream types:
For the German method sampling sites were assigned to the stream type “medium
38
Chapter 2: Intercalibration of assessment methods for macrophytes in lowland streams
sized lowland rivers of northern Germany” (Schaumburg et al., 2004). Since the stream
typology of the Netherlands is more complex sites have been allocated to eight
different national types for the Dutch index (Elbersen et al., 2003).
Table 13: Comparison of macrophyte abundance schemes
IBMR (FR) RI (DE) DMS (NL) MTR (UK)
Abun
danc
e cl
ass
Cov
er [%
]
Abun
danc
e cl
ass
(Koh
ler,
1978
)
Plan
t qua
ntity
(S
chne
ider
, 200
0)
Abun
danc
e cl
ass
Cov
er [%
]
Abun
danc
e cl
ass
Cov
er [%
]
1 < 0.1 1 1 1 < 0.1 2 0.1 – 1 2 8 2 0.1 - 1
3 1 - 2.5 1 < 5
4 2.5 - 5 3 1 – 10 3 27 5 5 - 10 6 10 - 25
4 10 – 50 2 5 - 50
7 25 - 50 4 64 8 50 - 75
5 > 50 5 125
3 > 50 9 > 75
The French, German and Dutch methods distinguish between five classes of ecological
quality (Table 14). Since the British MTR was developed to illustrate responses to
urban discharges by surveying two physically similar sites upstream and downstream
the method is not designed for classifying the ecological quality of rivers. For
interpretation purposes only, Holmes et al. (1999) suggest MTR boundary values to
determine if the investigated site is (1) ‘unlikely to be eutrophic’, (2) ‘likely to be either
eutrophic or at risk of becoming eutrophic’ or (3) ‘badly damaged by either
eutrophication, organic pollution, toxicity or physically damaged’. Here, the MTR value
discriminating between (1) and (2) was exemplarily used as the good-moderate
ecological status boundary.
2.2.3 Description of biotic metrics analysed to provide “common macrophyte metrics”
70 macrophyte metrics were analysed to detect “common metrics” enabling
intercalibration of national assessment methods (Table 15). These metrics cover the
categories “richness and diversity”, “composition and abundance”, “sensitivity and
tolerance”, and “ecosystem function”. The basic criterion for the selection of common
39
Chapter 2: Intercalibration of assessment methods for macrophytes in lowland streams
metrics was a correlation (R2 > 0.5; p < 0.05) of the metric with all assessment methods
evaluated in this study. As an additional criterion, redundant metrics were excluded
from further analysis. Of metric pairs with a coefficient of determination of > 0.65, the
metric showing the lesser correlation with the assessment methods was omitted.
Table 14: Class boundaries of the national assessment methods and derived reference values using the 95th percentile value of all survey sites (n.a. – not applicable).
Index IBMR (FR) RI (DE)3 DMS (NL) MTR (UK) High – good 15 0.5 0.8 n.a. Good – moderate 12 0.25 0.6 664 Moderate - poor 9 0.15 0.4 n.a. Poor - bad 7 0 0.2 n.a.
Literature source NF T90-395 (2003) Schaumburg et al.
(2005) van den Berg et al.
(2004) Holmes et al. (1999)
Reference (95th percentile) 13.2 0.86 0.42 60.4
2.2.4 Data preparation
The national assessment methods were manually calculated for each macrophyte
sample, with the exception of DMS (NL), which was calculated by the software QBWat
(Pot, 2005). Due to the minimum criteria for confidence specified by the German and
Dutch indices, they could not be determined for 15 and 9 sites, respectively. The index
values were converted into Ecological Quality Ratios, i.e. dividing the observed score
of each site by a reference value to normalise the output. The 95th percentile value of
all samples was chosen as index reference assuming that approximately five percent of
surveyed sites hold macrophyte communities in reference state.
2.2.5 Correlation and regression analysis: macrophyte assessment methods, potential common metrics and pressure gradients
The relationships between the four assessment indices were analysed and the strength
of correlation was specified by the “coefficient of determination” (R2). This measure was
also used to determine common macrophyte metrics suitable for intercalibration. Both
linear and nonlinear regression was tested using the software TableCurve 2D
(SYSTAT Software Inc., 2002).
3 Classification scheme relates to sites where only the Reference Index provides validated results within
the assessment method for aquatic flora. 4 Boundary based on recommendations for the interpretation of MTR scores to evaluate the trophic state
(Holmes et al., 1999; see text for details).
40
Chapter 2: Intercalibration of assessment methods for macrophytes in lowland streams
41
Table 15: Metrics tested with the macrophyte dataset. For taxa assignment to growth forms refer to Table 18 (# taxa - number of taxa, % - relative abundance, ca - composition/ abundance, f - functional, rd - richness/diversity, st - sensitivity/tolerance).
Name of metric Metric type
Reference
Proportion of community with preference for certain amount of water supply
Typical macrophytes (# taxa and %) f / rd / ca Holmes et al. (1999)
Species submerged (# taxa and %) f / rd / ca Species amphibious (# taxa and %) f / rd / ca Mosses and liverworts (# taxa and %) f / rd / ca Species terrestrial (# taxa and %) f / rd / ca
Szoszkiewicz et al. (2006a)
Diversity indices
Shannon diversity rd Shannon & Weaver (1949)
Simpson diversity rd Simpson (1949)
Evenness rd Pielou (1966)
Shannon diversity (growth forms) rd
Evenness (growth forms) rd
following Wiegleb (1991), van de Weyer (2003)
Morphological groups according to growth forms
Species anchored but with floating leaves or heterophyllus (# taxa and %) f / rd / ca Species floating free (# taxa and %) f / rd / ca
Szoszkiewicz et al. (2006a)
Growth forms (# taxa and %) f / rd / ca Growth form Myriophyllids (# taxa and %) f / rd / ca
Growth form Parvopotamids (# taxa and %) f / rd / ca
Growth form Peplids (# taxa and %) f / rd / ca
Growth form Vallisnerids (# taxa and %) f / rd / ca
Wiegleb (1991), van de Weyer (2003)
Reference and disturbance indicating taxa and growth forms of lowland streams
Disturbance indicating taxa (# taxa and %) st van de Weyer (2003)
Reference taxa (# taxa and %) st
Reference growth forms (# taxa and %) st
Disturbance indicating growth forms (# taxa and %) st
Ratio: reference taxa to disturbance indicating taxa (# taxa and %) st
Disturbance indicating growth form: Elodeids (# taxa and %) st
Disturbance indicating growth form: Lemnids (# taxa and %) st
Disturbance indicating growth form: Myriophyllids (# taxa and %) st
Disturbance indicating growth form: Parvopotamids (# taxa and %) st
Disturbance indicating growth form: Peplids (# taxa and %) st
Reference growth form: Batrachids (# taxa and %) st
Reference growth form: Ceratophyllids (# taxa and %) st
Reference growth form: Magnonymphaeids (# taxa and %) st
Reference growth form: Magnopotamids (# taxa and %) st
Reference growth form: Myriophyllids (# taxa and %) st
Reference growth form: Parvopotamids (# taxa and %) st
Reference growth form: Peplids (# taxa and %) st
Selected reference taxa (Potamogeton natans, P. polygonifolius, Nuphar lutea, Sagittaria sagittifolia, Sparganium emersum, Berula erecta) (# taxa and %)
st
Ratio: reference growth forms to disturbance indicating growth forms (# taxa and %)
st
following van de Weyer (2003)
Nitrogen indicating metric
Ellenberg_N st Ellenberg et al. (1992)
Chapter 2: Intercalibration of assessment methods for macrophytes in lowland streams
Physical-chemical, hydromorphological and land use/type data were used to construct
complex stressor gradients by means of principle components analysis (PCA). General
degradation gradients were derived from physical-chemical, hydromorphological and
land use data. In addition, separate degradation gradients were constructed via PCA,
using water chemistry, hydromorphological and microhabitat data. (see Hering et al.,
2006a). The results were used to test the response of the macrophyte methods to
individual pressure groups. Gradients best correlating to the macrophyte assessment
methods were determined.
2.2.6 Comparison of quality class boundaries
Two intercalibration approaches were applied in this study: (1) National quality classes
of the macrophyte methods were compared directly following the procedure described
in Chapter 1 of this thesis. The assessment method showing the highest correlation to
all other indices was used as a “common scale”. (2) The approach of indirect boundary
comparison (Buffagni et al., 2006) employed common metrics as response variables in
the regression analysis.
2.3 Results
2.3.1 Comparison of classification schemes
The classification results of the four methods applied differed noticeably. According to
the German method more than 50 percent of sites were in high and good status. The
French, British and Dutch methods assessed nearly all sites as of moderate or worse
quality (Figure 3).
Due to the different range of quality covered by the individual methods, the 95th
percentile value chosen as the reference value was allocated to different quality
classes for each of the four national classification schemes (Table 14): The reference
value was allocated as high quality in the German RI system, good quality in the
French IBMR system, and moderate quality in the Dutch DMS and British MTR
systems. Nevertheless, the reference obtained in the analysis for the British MTR
corresponded to the mean of top 10 percent MTR values for similar British lowland river
types given by Holmes et al. (1999).
42
Chapter 2: Intercalibration of assessment methods for macrophytes in lowland streams
M
M
M
G
G
H
M
H+G
0%
50%
100%
IBMR (FR) RI (DE) DMS (NL) MTR (UK)
Figure 3: Distribution of quality classes in the dataset resulting from four macrophyte assessment methods (H – high; G – good; M - moderate and worse). Quality classes of RI (DE) are based on the analysis of the Reference Index and additional criteria (Schaumburg et
al., 2004). The class boundary between high/good (H+G) and moderate quality of MTR (UK) is based on recommendations for the interpretation of MTR scores to evaluate the trophic state (Holmes et al., 1999; see text for details).
2.3.2 Correlation and regression analysis
Macrophyte assessment methods
The coefficients of determination given in Table 16 revealed the differences between
the four assessment methods. The French and British methods were most closely
related (R2 > 0.75). The German RI showed lower correlations with these methods,
especially with the French IBMR, while DMS (NL) was negatively correlated to all other
methods. Nonlinear regression generally resulted in higher coefficients of
determination. Between RI (DE) and MTR (UK) the difference between the two
regression models was R2 = 0.12.
Potential common macrophyte metrics
Of the 70 biotic macrophyte metrics tested, only Ellenberg_N correlated significantly to
all four assessment methods. For all four assessment methods nonlinear regression
yielded higher coefficients of determination to Ellenberg_N than linear regression.
43
Chapter 2: Intercalibration of assessment methods for macrophytes in lowland streams
While IBMR (FR), RI (DE) and MTR (UK) were negatively correlated to this metric, the
Dutch index values were positively related to Ellenberg_N.
None of the other biotic metrics showed strong correlations with all four macrophyte
assessment methods. For example, the richness measure “number of species” was
strongly related to the German and Dutch methods (Table 16). However, due to the
type of relation to the German RI (Figure 4) it could not be considered as a common
macrophyte metric, since the regression function was non-monotonic. Thus, for each
normalised value for “number of species”, two values of the German RI were possible.
0.0 0.2 0.4 0.6 0.8 1.0 1.2
RI (DE), DMS (NL)
0.0
0.2
0.4
0.6
0.8
1.0
1.2
num
ber
of s
peci
es
RI (DE) DMS (NL)
Figure 4: Nonlinear regression of German RI (solid line; R2 = 0.28) and Dutch DMS (dashed line; R2 = 0.59) against the number of species.
44
Chapter 2: Intercalibration of assessment methods for macrophytes in lowland streams
45
Table 16: Correlation and regression analysis of macrophyte assessment methods, selected macrophyte metrics and environmental gradients: Type of correlation (pos. - positive, neg. - negative) and coefficients of determination (R2) based on linear and nonlinear regression. Nonlinear R2 is only given if providing higher coefficients of determination (p < 0.05; n.s. – not significant).
IBMR (FR) RI (DE) DMS (NL) MTR (UK)
Type Linear Nonlinear Type Linear Nonlinear Type Linear Nonlinear Type Linear Nonlinear Macrophyte assessment methods IBMR (FR) pos. 1.00 1.00 pos. 0.22 0.31 neg. 0.06 - pos. 0.76 0.79 RI (DE) pos. 0.22 0.26 pos. 1.00 1.00 - n.s. n.s. pos. 0.41 - DMS (NL) neg. 0.06 0.10 - n.s. 0.15 pos. 1.00 - neg. 0.05 0.07 MTR (UK) pos. 0.76 0.77 pos. 0.41 0.53 neg. 0.05 - pos. 1.00 - Selected macrophyte metrics Ellenberg_N neg. 0.46 0.56 neg. 0.46 0.58 pos. 0.05 0.11 neg. 0.69 0.70 Number of species neg. 0.04 0.06 - n.s. 0.28 pos. 0.56 0.59 - n.s. 0.06 Disturbance indicating growth forms (%) neg. 0.07 - - n.s. n.s. pos. 0.56 - neg. 0.05 n.s.
Environmental gradients Pollution/ eutrophication neg. 0.46 - neg. 0.14 0.22 pos. 0.09 0.10 neg. 0.51 0.52
General degradation - n.s. n.s. - n.s. n.s. neg. 0.41 0.42 - n.s. n.s.
Chapter 2: Intercalibration of assessment methods for macrophytes in lowland streams
46
X
X
The DMS (NL) showed coefficients of determination of R2 > 0.5 with several functional
metrics (e.g. “relative abundance of disturbance indicating growth forms”, “relative
abundance of disturbance indicating growth form: Lemnids” and “number of selected
reference taxa”).
Environmental gradients (PCA)
The French, German and British methods related most strongly to the PCA gradient
reflecting water chemistry (“pollution/eutrophication”, PCA axis 1, Eigenvalue: 0.527;
Table 16). The Dutch method was correlated with “general degradation” including
chemical, hydromorphological and land use parameters (PCA axis 1, Eigenvalue:
0.287). Coefficients of determination of the regression analysis are listed in Table 16
(see Hering et al., 2006a for details of the gradients).
Table 17: EQR values of the high-good (H|G) and good-moderate (G|M) quality class boundaries transferred into MTR and Ellenberg_N scales via nonlinear regression analysis. For each value derived by regression the 95 percent confidence interval is specified (n.a. –
not applicable). (1) f(x) = a + b·x1.5; (2) f(x) = a + b·x3
IBMR (FR) RI (DE) MTR (UK)
Class boundary
Common scale
Equa
tion
Boun
dary
va
lue
95%
co
nfid.
Equa
tion
Boun
dary
va
lue
95%
co
nfid.
Equa
tion
Boun
dary
va
lue
95%
co
nfid.
MTR (1) 1.497 0.150 (2) 0.638 0.056 H|G
Ellenberg_N (2) 1.185 0.287 (2) 0.394 0.079 n.a.
MTR (1) 0.820 0.044 (2) 0.565 0.067 - 1.094 - G|M
Ellenberg_N (2) 0.638 0.103 (2) 0.294 0.094 (1) 0.911 0.143
2.3.3 Direct comparison of quality class boundaries
The British MTR correlated best with all other methods and was therefore used as the
“common scale” according to Chapter 1 of this thesis. Due to its weak relationship with
any of the other macrophyte methods, the Dutch DMS was not included in direct class
boundary comparison. Considering the 95 percent confidence intervals, direct
comparison revealed large differences in national definitions of the high-good quality
boundary (> 0.6 MTR units on average,
Table 17). The differences between the good-
moderate boundaries were smaller (< 0.3 MTR units on average). The mean value of
confidence intervals amounted to 0.079 MTR units.
Chapter 2: Intercalibration of assessment methods for macrophytes in lowland streams
The nonlinear regression graph (Figure 5) shows decreasing slope values with
increasing deviation of IBMR (FR) and RI (DE) from the reference state. Especially in
the lower range of the RI (DE), the British MTR was not responding to changes of the
German method. Therefore, the high-good and good-moderate class boundary
intervals of RI (DE) transferred into MTR scale were overlapping (cf. Table 17).
0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6
IBMR (FR), RI (DE)
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
MT
R (
UK
)
IBMR (FR)
RI (DE)
Figure 5: Nonlinear regression of French IBMR (solid line; R2 = 0.77) and German RI (dashed line; R2 = 0.53) against British MTR.
2.3.4 Indirect comparison of quality class boundaries using Ellenberg_N as common macrophyte metric
The high-good boundary comparison of the French and German method using
Ellenberg_N resulted in a difference of > 0.4 units. For the German and British method,
confidence intervals of the good-moderate class boundaries shared similar ranges
when compared via Ellenberg_N. The average confidence interval amounted to 0.141
units.
47
Chapter 2: Intercalibration of assessment methods for macrophytes in lowland streams
As observed in the “direct comparison approach” the quality class boundaries of RI
(DE) showed overlapping confidence ranges using Ellenberg_N (Table 17). Regression
analysis disclosed a similar type of relation between the German method and each of
MTR and Ellenberg_N (Figure 6).
0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6
IBMR (FR), RI (DE), MTR (UK)
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
Elle
nber
g_N
IBMR (FR)MTR (UK)RI (DE)
Figure 6: Nonlinear regression of French IBMR (solid line; R2 = 0.56), German RI (dashed line;
R2 = 0.58) and British MTR (dotted line; R2 = 0.70) against Ellenberg_N.
2.4 Discussion
The obviously different quality classes of the sites assessed with the four methods
(Figure 3) reveal that intercalibration efforts for macrophyte methods are indispensable.
Starting from this conclusion I applied analytical methods currently used in
intercalibration of benthic invertebrate systems (Buffagni et al., 2006; see also
Chapter 1 of this thesis) to compare quality class boundaries of macrophyte
assessment methods.
48
Chapter 2: Intercalibration of assessment methods for macrophytes in lowland streams
2.4.1 Testing of intercalibration approaches
This study discloses difficulties in adopting commonly used intercalibration approaches
to macrophyte based assessment methods. Direct comparison of class boundaries
only yielded sound results between the closely related methods IBMR (FR) and MTR
(UK). These two indices share many common indicator species (Szoszkiewicz et al.,
2006a) whose indicator values correlate strongly (R2 = 0.61). The sound correlation of
the German RI with MTR (UK) seems to allow for direct boundary comparison.
However, the specific nonlinear character of this relationship impedes significant
resolution between the good quality boundaries, thus making direct comparison of
these methods impossible. The low correlations of DMS (NL) with all other national
assessment methods exclude this index from further intercalibration analysis.
Against this background I tested whether intercalibration could be accomplished using
common metrics (Buffagni et al., 2006). My analysis showed that none of the tested
macrophyte metrics met the common metric criteria for all assessment methods. Only
Ellenberg_N showed strong relationships with at least three methods. The metric is
based on the response of higher plants to nitrogen compounds (nitrate and/or
ammonium) and, thus, corresponds to trophic categories and to general nutritional
conditions in the rivers that are represented with a broad gradient in the dataset (see
Table 11). The French, German and British methods relating to this potential common
metric also respond significantly to the abiotic PCA gradient reflecting organic pollution
and eutrophication. These findings underline the general ability of macrophyte methods
to assess the trophic status of rivers. While Holmes et al. (1999) designed the British
MTR for this specific purpose, the German method in particular is aimed at detecting
“general degradation”, i.e. the level of deviation from a reference community
(Schaumburg et al., 2004).
Like in direct comparison, DMS (NL) cannot be included in the intercalibration analysis
using common metrics. Although it shares objectives with the German method
(unspecific pressure assessment based on type specific macrophyte communities), I
found no biotic metric suitable for intercalibration. Either different types of relation (cf.
Figure 6) or no common relationship at all, limits the applicability of the common metric
approach. DMS (NL) is characterised by strong relations to richness and diversity
measures and, most remarkably, by positive correlations with metrics indicating
49
Chapter 2: Intercalibration of assessment methods for macrophytes in lowland streams
disturbance in lowland streams of North-Rhine Westphalia (Western Germany; Table
18; van de Weyer, 2003). In this respect, the broad spectrum of environmental factors
influencing the occurrence of macrophytes in streams on various spatial scales
(Wiegleb, 1988) may confine the validity of indicator species to narrow geographic
regions. Furthermore, Korte & van de Weyer (2005) observed that, in two separate
methods for the assessment of German lowland streams, indicative characteristics of
macrophyte species are evaluated differently. Nevertheless, the weak but significant
positive correlation of the Dutch method with Ellenberg_N points at basic differences in
the conception of the reference state. This is also indicated by the negative correlation
of DMS (NL) to the “general degradation” gradient. However, since the dataset
analysed covers only sites of moderate or worse status according to the Dutch
classification system the validity of my findings is limited to a restricted range of quality.
Further incomparability results from the different calculation methods. The French,
German and British indices are calculated by weighted average equations, yielding
values less influenced by the species richness of the site. Abundance scores are
accounted by multiplication by the indicator values. Results of DMS (NL) are obtained
by summation of taxa scores, whose values depend on the relative abundance of the
species. For certain species in specific river types this score value decreases with
increasing abundance and vice versa.
National assessment methods for all biological quality elements will need to assess
ecological quality in a general way; therefore, the intercalibration exercise of
macrophyte-based methods has to simultaneously target the effects of different types
of degradation. The selection of common intercalibration metrics should thus respond
to general degradation (see also Buffagni et al., 2005 using common metrics for
intercalibration of invertebrate-based methods). I tested a broad range of general and
specific macrophyte metrics covering biotic parameters like taxonomic composition and
abundance, richness and diversity, and functional groups (Table 15). Since none of the
metrics analysed qualified for intercalibration purposes, further research to produce
suitable common macrophyte assessment metrics is indispensable.
50
Chapter 2: Intercalibration of assessment methods for macrophytes in lowland streams
51
Table 18: Reference taxa and disturbance indicating taxa of lowland streams and their growth forms (following van de Weyer 2003).
Reference taxa Growth form Chara fragilis Desvaux Chara sp. L. ex Vaillant Nitella flexilis C. A. Ag. Nitella sp. C. A. Ag.
Charids
Ceratophyllum submersum L. Ceratophyllids Berula erecta (Huds.) Coville Juncus bulbosus L.
Herbids
Nuphar lutea (L.) Sibth. & Sm. Nymphaea alba L. Persicaria amphibia (L.) Gray Ranunculus flammula L.
Magnonymphaeids
Potamogeton alpinus Balbis Potamogeton gramineus L. Potamogeton natans L. Potamogeton polygonifolius Pourret Potamogeton lucens L. Potamogeton obtusifolius Mert. & Koch Potamogeton perfoliatus L. Potamogeton praelongus Wulfen
Magnopotamids
Myriophyllum alterniflorum DC. Myriophyllum verticillatum L. Utricularia intermedia Hayne Utricularia vulgaris L.
Myriophyllids
Potamogeton berchtoldii Fieber Potamogeton compressus L. Potamogeton filiformis Pers.
Parvopotamids
Callitriche cophocarpa Sendtn. Callitriche hamulata Kutz ex W.D.J. Koch Callitriche platycarpa Kütz.
Peplids
Alisma plantago-aquatica L. Sagittaria sagittifolia L. Sparganium emersum Rehmann Sparganium erectum L. Sparganium sp. L.
Vallisnerids
Disturbance indicating taxa Ceratophyllum demersum L. Ceratophyllum demersum var. apiculatum Cham. Ceratophyllids
Elodea canadensis Michx. Elodeids Lemna gibba L. Lemna minor L. Spirodela polyrhiza (L.) Schleid
Lemnids
Myriophyllum spicatum L.5 Ranunculus fluitans Lamk.5 Myriophyllids
Potamogeton crispus L. Potamogeton pectinatus L. Potamogeton pusillus L. Potamogeton trichoides Cham. & Schltdl. Zannichellia palustris L.
Parvopotamids
Callitriche obtusangula Le Gall Peplids
5 According to van de Weyer (2003) these species indicate increased current velocity (e.g. due to channel
straightening).
Chapter 2: Intercalibration of assessment methods for macrophytes in lowland streams
2.4.2 Implications for the macrophyte intercalibration exercise
This chapter presents preliminary results which may become relevant in the further
discussion of macrophyte intercalibration. Nevertheless, several procedural
requirements of the official intercalibration exercise are not met: (1) The international
STAR dataset covers different biogeographical regions. Therefore, the applicability of
national methods may be affected because the assessment is adjusted to the regional
flora and the indicative characteristics of its macrophyte species. (2) Since
macrophytes were surveyed according to a standard procedure (Furse et al., 2006),
national survey techniques and their effect on the taxa list are neglected. (3) I based
my analyses on macrophytes only, whereas two of the methods examined, RI (DE) and
DMS (NL) are designed to assess the broader “aquatic flora”, including phytobenthos.
Considering these items, the following implications for the macrophyte intercalibration
exercise can, however, be stated.
The comparison of quality classes for European river assessment methods using
benthic invertebrates was successfully accomplished (Owen et al., 2010). This can
substantially be attributed to the strong relationships of the methods (see Chapter 1 of
this thesis), their focus on similar pressures and their common tradition. In the view of
the present study, the practicability of the analytical approaches applied to the
intercalibration of macrophyte methods (direct comparison, use of common metrics) is
questionable. Two main factors that complicate comparisons between methods are (1)
differently defined reference conditions and (2) gaps in knowledge about pressure-
impact relationships. The delineation of reference communities, particularly for the
medium-sized lowland rivers of Central Europe, is difficult due to the lack of existing
reference sites. Therefore, expert opinion is used to estimate natural conditions in the
lowlands. Furthermore, the Dutch and German methods both define reference states
via index scores, but include diverse macrophyte species and apply different formulae.
The lack of knowledge about pressure-impact relationships may generally impede the
intercalibration of macrophyte methods. While higher plants are well known for their
response to nutrient pollution, the effect of other impairments on the community is has
little been studied (Kelly & Whitton, 1998; Janauer, 2001). This also delimits the
availability of appropriate common assessment metrics. This study demonstrates on
the one hand that intercalibration of methods specifically addressing eutrophication is
52
Chapter 2: Intercalibration of assessment methods for macrophytes in lowland streams
possible but, on the other hand, it also highlights deficiencies for the coming
macrophyte intercalibration exercise.
Since the intercalibration of national methods has to be accomplished by 2011,
scientific activities at the European level are currently being carried out to fulfil these
legal requirements. Thus, the intercalibration task has initiated a process of Europe-
wide discussion on ecological quality and the harmonization of its assessment. Tailor-
made approaches for each biological element are required relying on national expertise
and international coordination. As a first step towards intercalibration of macrophyte
methods in Central Europe, I propose to compile an international database including
national data on macrophytes and abiotic pressures taken from sites at common
intercalibration types. Since field procedures of the countries involved are very similar
(visual survey of 100 m stream sections), this will enable more extensive analyses of
the relation between the assessment indices and the definition of the reference state.
The outcome may necessitate detailed bilateral discussion on the assessment results
at individual sites. This time consuming approach has already yielded results in a
preliminary intercalibration study between macrophyte methods of Austria and
Germany (Pall et al., 2005).
With regard to the multitude of issues to be addressed in the near future,
intercalibration represents a major chance for the implementation of harmonized quality
standards at the European level beyond the short timeframe given by the Directive. For
macrophyte based ecological quality assessment in particular, which is still in its early
stages in Europe, communality can be gained by maintaining and extending
international collaboration to enhance scientific exchange and trigger common outputs.
53
Chapter 3: Establishing common grounds in European macrophyte assessment for rivers
54
3 Towards harmonization of ecological quality classification: establishing common grounds in European macrophyte assessment for rivers
3.1 Introduction
River macrophyte communities are determined by the characteristics of the local
habitat in which they occur, namely light availability, current velocity, sediment patterns
and nutrient supply. Biogeographical zone, catchment geology and stream hydrology
establish the large-scale framework influencing occurrence and abundance of
macrophytes (Lacoul & Freedman, 2006). Since most of these factors can be subject to
anthropogenic alteration, macrophytes are effective bioindicators that respond to
various human pressures by a change in cover, richness or taxonomical composition
(e.g. Baattrup-Pedersen & Riis, 1999, Ferreira et al., 2005, Szoszkiewicz et al., 2006a).
Combined with benthic microalgae, macrophytes thus form an obligatory element in the
monitoring of ecological river quality as stipulated by the EU Water Framework
Directive 2000/60/EC (WFD). For discrete stream types the taxonomical composition
and abundance of macrophytes are appraised by biological assessment methods. The
status observed at the monitored river stretch is compared to the status expected
under near-natural conditions. The resulting Ecological Quality Ratio (EQR) evaluates
the river quality in a score ranging from 0 (worst status) to 1 (reference status). This
range is divided into five classes of ecological quality: high, good, moderate, poor and
bad.
The WFD requires that all water bodies should attain good ecological status within the
near future. However, countries obliged to fulfil these requirements are applying
different assessment methods. To set a common level of ambition in reaching the
WFD’s objective good ecological status is harmonized through the so-called
“intercalibration exercise” (Heiskanen et al., 2004). The specific challenge of this
exercise is to calibrate the national interpretations of good ecological status. Although
the WFD provides general guidelines for the high, good and moderate quality status,
the practical implementation of these normative definitions has to be compared
between the various countries.
Chapter 3: Establishing common grounds in European macrophyte assessment for rivers
For benthic diatoms (Kelly et al., 2008) and benthic invertebrates (Owen et al., 2010)
the national assessment methods were intercalibrated by the use of common metrics
(Buffagni et al., 2007). These metrics allow the national definitions of good ecological
status to be compared across different countries and stream types. Common metrics
take advantage of similar assessment principles that all national methods have in
common. For instance, anthropogenic pressure generally causes a decrease of taxa
richness in invertebrate communities, making the total number of taxa a suitable
common metric (Buffagni et al., 2005). However, in Chapter 2 I reported on difficulties
in finding common metrics for the intercalibration of river macrophyte methods.
Differing national assessment concepts were identified: Some countries focus on the
appraisal of specific pressures, especially nutrient enrichment, while others emphasize
assessment of general degradation.
This fundamental difference raises the question, if any conceptual similarities exist
between the national macrophyte classifications. Expert discussions confirmed a
common notion of type-specific macrophyte communities at high ecological status (Birk
et al., 2007a). Motivated by this finding, the present study investigates whether this
common notion can be empirically defined. In particular, my work is based on the
following hypotheses:
Certain macrophyte communities that occur in a common stream type are
classified in high quality status by the majority of national assessment methods.
These communities feature species that are regarded as indicators of near-natural
conditions across national methods.
Following this concept general disturbance indicators can also be identified based
on data of communities commonly classified in poor or bad quality status.
These hypotheses were tested by applying seven macrophyte assessment methods to
an international dataset that covered three European stream types. I correlated the
abundance of individual macrophyte taxa to the average national EQR per survey and
thus gained indicators of a common high or poor quality status. Based on these
outcomes I
(1) describe the macrophyte communities of each stream type under near-natural
and degraded conditions,
55
Chapter 3: Establishing common grounds in European macrophyte assessment for rivers
(2) develop a common macrophyte metric and relate it to the national methods,
(3) propose amendments to certain national methods in order to improve their
relationship with the common metric and
(4) identify type-specific reference values to convert the common metric scores into
EQRs.
3.2 Methods
3.2.1 Data basis
In this study data on taxonomic composition and abundance of river macrophytes was
used. Sampling sites were located on rivers belonging to three common stream types
(ECOSTAT, 2004b) that were shared by twelve countries in Central and Western
Europe and the Baltic region (Table 19). The common stream types were delineated by
their altitude, catchment size, geology, substrate composition and alkalinity. The types
covered small to medium-sized streams in the lowlands and small streams in the
mountains.
Table 19: Characterisation of the common stream types
Stream type abbreviation Common stream type
Catchment area [km2] Altitude [m] Geology Channel substrate
Alkalinity [meq/l]
R-C1x2 Small lowland sandy streams 10 – 100 < 200 Siliceous Sand > 1
R-C3 Small mid-altitude siliceous streams
10 – 100 200 - 800 Siliceous Boulders, cobbles
and gravel < 0.4
R-C4x2 Medium-sized lowland steams 100 - 1000 < 200 Mixed Gravel and sand > 2
In total, 609 macrophyte surveys were provided by the countries listed in Table 20. The
data originated from national monitoring programmes or scientific projects (e.g. Furse
et al., 2006). Countries applied national macrophyte survey protocols that were in line
with the requirements of the European Standard EN 14184:2003. Representative river
stretches were visually inspected by wading, diving or boating, using rake, grapnel or
aqua-scope where necessary. Representative sites spanned about 100 metres of river
length.
The macrophyte abundance was recorded in different scales (Table 21). Most
countries specified the abundance as relative coverage of the surveyed area. Percent
56
Chapter 3: Establishing common grounds in European macrophyte assessment for rivers
values were graded into five, seven or nine classes. The Austrian method combined
the number of single plant records per surveyed section and the plant quantity per
habitat following Kohler (1978) in a five-class scheme. Germany estimated the plant
quantity (Melzer et al., 1986) in one of five different classes. The Dutch abundance
data were given in various scales (Braun-Blanquet, 1928, Tansley, 1946).
Table 20: Number of macrophyte surveys used in the analysis, listed per country and common stream type
Stream type abbreviation Country Number of surveys Belgium (Flanders) 105 Belgium (Wallonia) 1 Denmark 15 Germany 38 Latvia 15 Lithuania 1 Netherlands 14 Poland 11
R-C1x2
Total number 200 Austria 31 Belgium (Wallonia) 43 Czech Republic 13 France 78 Germany 81 Great Britain 33
R-C3
Total number 279 Belgium (Flanders) 15 Denmark 4 Germany 32 Great Britain 3 Latvia 29 Lithuania 9 Luxemburg 3 Netherlands 8 Poland 27
R-C4x2
Total number 130
3.2.2 National assessment methods
Seven countries participated in this exercise with their national assessment methods
(Table 22). Most methods focused on the assessment of specific human pressure
(Austria, France, Great Britain, Poland, Wallonia). The principal component of this
approach was formed by a list of indicator taxa graded by their sensitivity, mainly to
57
Chapter 3: Establishing common grounds in European macrophyte assessment for rivers
nutrient enrichment. Numerical assessment results were obtained by computing a
sensitivity metric, i.e. the average score of indicative species weighted by their
abundance. In case of the Austrian, French and Wallonian metrics this also included a
factor considering the taxon’s ecological amplitude.
Table 21: Conversion table of national macrophyte abundance classes into the international abundance scale
International abundance scale Country 1st class
(rare) 2nd class
(occasional) 3rd class
(frequent) 4th class
(abundant) 5th class
(very abundant) Austria Belgium (Wallonia) Czech Republic Denmark France Germany Latvia Lithuania Luxembourg
1 2 3 4 5
Belgium (Flanders) 1 2 3 4 5 6 7
Great Britain Poland 1 2 3 4 5 6 7 8 9
The Netherlands (Braun-Blanquet, 1928)
1 2 3 4 5 6 7 8 9
The Netherlands (Tansley, 1946) 1 2 3 4 5 6 7 8
The Flemish and German methods were oriented towards the indication of non-specific
anthropogenic disturbance. Besides sensitivity measures these methods considered
additional metrics, such as richness of macrophyte growth forms, or taxa richness and
dominance. The basic element of the German Reference Index (RI) was the type-
specific definition of reference and non-specific disturbance indicating taxa. The RI was
a numerical expression of the relation of both response groups at a river site. The
supplementing assessment criteria directly contributed to the score of the RI. The
Flemish method integrated three metrics in the appraisal of ecological status by the
“one out – all out” principle: The type-specific index for water vegetation, the
perturbation index for water vegetation and the richness of various growth forms.
Based on the experiences gained in earlier intercalibration studies (Birk et al., 2007a)
the assessment of macrophyte growth form was not considered in the main analysis.
58
Chapter 3: Establishing common grounds in European macrophyte assessment for rivers
However, I additionally tested the performance of the Flemish method including the
growth form metric.
Table 22: National assessment methods using macrophytes in rivers
Country Name of method Intercalibrated assessment metric(s)
Relevant stream type(s)
Literature reference
Austria Austrian Index for Macrophytes in Rivers (AIM Rivers)
Single metric combining ecological preference and abundance
R-C3 BMLFUW (2006a)
Belgium (Flanders)
MAFWAT (Makrophyten Waterlopen)
(1) Type specific index for water vegetation (TSw) (2) Perturbation index (organic pollution, eutrophication) for water vegetation (Vw)
R-C1x2, R-C4x2 Leyssen et al. (2005)
Belgium (Wallonia) France
Indice Biologique Macrophytique en Rivière (IBMR)
Single metric combining occurrence (indicator value per taxon), ecological amplitude and abundance
R-C3, R-C4x2 (only France) NF T90-395:2003
Germany
Deutsches Bewertungsverfahren für Makrophyten und Phytobenthos (PHYLIB)
Index relating Species Response Groups (Reference, Disturbance, Indifferent) plus additional criteria for R-C3: acidification module R-C4x2: evenness, number of submerged taxa, ratio of Myriophyllum spicatum and Ranunculus sp.
R-C1x2, R-C3, RC4x2
Schaumburg et al. (2006)
Great Britain
River Nutrient Macrophyte Index (RNMI)
Single metric combining occurrence (indicator value per taxon) and abundance
R-C3, R-C4x2 Willby et al. (2006)
Poland Macrophyte Index for Rivers (MIR)
Single metric combining occurrence (indicator value per taxon) and abundance
R-C1x2, R-C4x2 Szoszkiewicz et al. (2006b)
3.2.3 Intercalibration analysis
Preparatory steps of the intercalibration analysis comprised the harmonization of the
macrophyte taxonomy, especially the identification of synonymous taxon nominations
due to different reference literature used by the countries. Furthermore, the abundance
data were converted from the national into an international abundance scale (Table
21). A level of aquaticity was assigned to each macrophyte taxon that characterized the
taxon’s affinity to water (C. Chauvin, pers. comm.). Table 23 provides an overview of
the different aquaticity levels used in this study.
The national metrics were applied to the macrophyte survey data. Using the national
stream-type specific reference values all metric results were transformed into
59
Chapter 3: Establishing common grounds in European macrophyte assessment for rivers
Ecological Quality Ratios (EQR). The ecological quality of each survey was classified
according to the national methods. Those surveys were identified that the majority of
methods classified in high status and none of the methods in moderate or worse status.
In the following these surveys are named “common high status sites”.
Table 23: Level of aquaticity characterizing the affinity of the macrophyte taxon to water according to C. Chauvin (pers. comm.)
Level of aquaticity Description
1 Exclusively aquatic species (or mainly aquatic in regular conditions).
2 Aquatic taxon with common terrestrial forms or truly amphibious (common aquatic forms as well as terrestrial forms).
3 Supra-aquatic bryophytes and lichens. Commonly submerged a part of the hydrological cycle. 4 Helophytes or Amphiphytes. Erected forms with basis commonly inside water. 5 Hygrophilous taxa. Possibly submerged (at least the basis) a part of the year.
6 Bank, wood, grasslands or ruderal herbaceous species. May be found in water accidentally or in conditions of high flow.
7 Woody riparian species. May be flooded temporarily. 8 Brackish water or salty marshes species.
For each common stream type the values of the national EQRs were normalized to a
scale ranging from 0 to 1. These normalized values were then averaged for each
survey. In case of the two Flemish sensitivity metrics the lowest value per survey was
taken (“worst case”) according to the national protocol (Leyssen et al., 2005). As a
result, a mean index score was assigned to each survey that was composed of the
average of normalized national metric values. Each national metric therefore had an
equal contribution to the mean index score.
In a next step this mean index was correlated with the abundance of macrophyte taxa
recorded in the surveys using the international abundance scale and including zero
abundance. The relation of taxa abundance to the mean index was quantified by
Spearman’s coefficient of correlation. The analysis yielded a coefficient for each taxon
and comprised a spectrum of values identifying taxa correlated – either positively or
negatively – or not correlated to the average national assessment results. Positive
correlation meant: the higher the mean index, the higher this taxon’s abundance.
Negative correlation meant: the lower the mean index, the higher this taxon’s
abundance.
60
Chapter 3: Establishing common grounds in European macrophyte assessment for rivers
I used the correlation coefficients to define taxon-specific indicator scores. These
scores were assigned only to taxa records at species level except for selected algae
and mosses. Taxa with only one record in the database or taxa with an aquaticity level
> 5 were given no indicator score. I rescaled the coefficients of scoring taxa based on
the maximum or minimum correlation separately for each common stream type. For
instance, if the range of correlation coefficients was from -0.3 to +0.5 I rescaled from
-0.5 to +0.5 which produced an actual range running from -0.6 to +1.0 with a zero score
coinciding with a zero correlation. Based on the indicator scores I could describe the
common type specific macrophyte community occurring at reference and degraded
conditions.
The indicator scores were used in a common type-specific, weighted average metric,
the so-called “macrophyte Intercalibration Common Metric” (mICM) following the
terminology of Buffagni et al. (2005):
i
iix abd
abdsmICM
)*(,
where mICMx was the macrophyte Intercalibration Common Metric value of a survey
at the common stream type x,
si was the taxon specific correlation value of the i-th taxon and
abdi was the international abundance class of the i-th taxon.
The mICM was plotted against each national metric per common stream type. Linear
regression models were applied and the resulting coefficients of determination (R2)
were checked. In case of R2 values < 0.5 I compared the mICM scoring taxa list and
the national indicator list. Obvious discrepancies between both lists were adjusted by
proposing small amendments to the national list. However, I focussed only on those
amendments that allowed for an increase of the R2 value ≥ 0.5 in the regression
analysis. Furthermore, to demonstrate the performance of the Flemish method
including the growth form metric the mICM was also correlated with the worst case of
the three Flemish metrics.
For each stream type I determined the median mICM value from the pool of common
high status sites. This value served as the common stream type-specific reference by
which the mICM was transformed into an EQR. To characterize the distribution of
61
Chapter 3: Establishing common grounds in European macrophyte assessment for rivers
mICM EQR values among the common high status sites I calculated the 5th and 10th
percentile values. Lower percentiles, such as these have been widely used in
invertebrate classification as a statistical basis for the high-good boundary (e.g. Clarke
et al., 1996).
3.3 Results
For each common stream type Table 24 displays the range of coefficients resulting
from correlating the mean index and taxa abundances. In addition, those taxa best
correlated to the mean index (either positively or negatively) are listed. In total, 102
(R-C1x2), 140 (R-C3) and 110 (R-C4x2) indicator taxa were defined. All indicator taxa,
their level of aquaticity and rescaled indicator scores are shown in the Appendix.
Table 24: Range of Spearman’s correlation coefficients (CorrCoef) and taxa showing highest
positive (+) and negative (-) correlation of abundance to the mean index gradient
Taxa best correlated to the mean index Stream type CorrCoef range + -
R-C1x2 0.46 to -0.34 Callitriche hamulata Kuetz. ex W.D.J. Koch, Caltha palustris L., Cardamine amara L.
Lemna minor L., Potamogeton pectinatus L., Potamogeton perfoliatus L.
R-C3 0.61 to -0.53 Pellia epiphylla L. Corda, Racomitrium aciculare (Hedw.) Brid., Scapania undulata (L.) Dum
Amblystegium riparium (Hedw.) B.S.G., Cladophora sp. Kuetz., Phalaris arundinacea L.
R-C4x2 0.55 to -0.51 Fontinalis antipyretica Hedw., Hildenbrandia sp. Nardo, Potamogeton alpinus Balbis
Lemna minor L., Potamogeton pectinatus L., Sagittaria sagittifolia L.
Coefficients of determination (R2) obtained in the regression analyses of the national
metrics against the mICM range from 0.28 to 0.78. On average, the British metric is
best correlated with the mICM while the German method shows the weakest overall
relationship. Highest R2 values are gained in the analysis of the mountain type R-C3.
To improve weak relationships of the mICM with the national metrics I adjusted the
national indicator lists of Flanders (including additional disturbance taxa in metric Vw
for type R-C1x2) and Germany (re-scoring of indicator taxa for type R-C4x2). Both
adjustments lead to coefficients of determination ≥ 0.5 in the regression analysis.
Adjustments and results of the regression analyses are specified in Table 25.
62
Chapter 3: Establishing common grounds in European macrophyte assessment for rivers
In total, 111 common high status sites are identified, with most of these relating to the
R-C3 mountain rivers (Table 26). The mICM median values of these sites show a clear
difference, distinguishing between the two lowland types on one hand and the
mountain rivers on the other. However, the percentiles of the mICM EQR value
distributions are rather similar, ranging from 0.79 to 0.84. This indicates that the spread
of values is consistently narrow, and that the unit of turnover of the reference
population (~0.2) would be appropriate for establishing a series of lower class
boundaries.
Table 25: Results of the linear regression analysis of mICM against the national metrics
R2 (orig.) – coefficient of determination using national index with original indicator taxa list, R2 (amend.) – coefficient of determination using national index with amended indicator taxa list
Stream type Country R2 (orig.) R2 (amend.) Specification of amendment
Belgium (Flanders) 0.28 (0.21)
0.50 (0.24)
Additional disturbance indicators in metric Vw: Nymphoides peltata (Gmel.) Kuntze, Potamogeton berchtoldii Fieber, Potamogeton crispus L., Potamogeton perfoliatus L., Rorippa amphibia (L.) Besser, Sagittaria sagittifolia L., Sparganium emersum Rehmann
Germany 0.55 - -
R-C1x2
Poland 0.62 - - Austria 0.74 - - Belgium (Wallonia) 0.77 - - France 0.76 - - Germany 0.54 - -
R-C3
Great Britain 0.78 - -
Belgium (Flanders) 0.59 (0.02)
- -
Germany 0.17 0.59 Re-scoring of indicator taxa: Fontinalis antipyretica Hedw. (Reference), Lemna minor L. (Disturbance)
France 0.58 - - Great Britain 0.62 - -
R-C4x2
Poland 0.58 - -
Table 26: Number of common high status sites (N), mICM reference values (REF), and 5th and
10th percentile values of the mICM EQR distributions
Stream type N REF 5th percentile 10th percentile R-C1x2 27 0.15 0.83 0.84 R-C3 63 0.36 0.79 0.83 R-C4x2 21 0.13 0.80 0.84 all data combined 111 - 0.79 0.83
63
Chapter 3: Establishing common grounds in European macrophyte assessment for rivers
3.4 Discussion
3.4.1 Description of stream type-specific macrophyte communities
The identification of common high status sites confirms the first hypothesis. For each
stream type several surveys are classified in high quality status by most of the national
methods. The smaller relative number of such surveys at lowland sites can be
attributed to the generally more degraded lowland conditions. The strong linear relation
of the abundance of certain macrophyte taxa with the mean index supports the
existence of common indicator species. These findings allow stream type-specific
communities and their environment to be defined under near-natural and degraded
conditions.
The highest quality R-C1x2 sites feature a combination of submerged rooted aquatic
species of which Callitriche hamulata, Potamogeton natans and Sparganium emersum
are by far the commonest. Scarcer associated species, which characterise high status
R-C1x2 rivers include Potamogeton alpinus, Myriophyllum alterniflorum, Elodea
canadensis, various other Callitriche spp. and Ranunculus peltatus. Emergent
vegetation is dominated by Phalaris arundinacea, Sparganium erectum and
Phragmites australis, the latter characteristic of high status sites. There are a range of
moderate- to small-sized emergent species, of which Persicaria hydropiper, Myosotis
scorpioides, Glyceria fluitans, Berula erecta, Mentha aquatica and Veronica anagallis-
aquatica are the most abundant, but it is the less frequent elements, such as
Cardamine amara and Caltha palustris that are characteristic. This assemblage is most
likely to be associated with small, active, mesotrophic, shallow, sand-dominated, clear
water, moderately fast flowing, partially-shaded streams. The very limited number of
characteristic species suggests that this is a type with several geographically distinct
variants under high status conditions. With declining quality there is a shift to a
community dominated by Sparganium emersum, alongside a range of species that are
absent from or much scarcer in the highest status sites, including Potamogeton
pectinatus, P. trichoides, P. perfoliatus and P. crispus, and the duckweeds Lemna
minor and L. minuta. Among the emergent species that overlap with high status sites
Sparganium erectum, Persicaria hydropiper, Phalaris arundinacea, Phragmites
australis, Myosotis scorpioides and Berula erecta are all much reduced, and are
typically replaced by Rorippa amphibia, Glyceria aquatica, Sagittaria sagittifolia and
Alisma plantago-aquatica. This change in structure suggests a shift to silty, stable,
64
Chapter 3: Establishing common grounds in European macrophyte assessment for rivers
eutrophic, slow flowing, turbid conditions in managed or regulated channels with
degraded riparian habitat.
High quality R-C3 rivers feature a combination of leafy liverworts (Scapania undulata or
Chiloscyphus polyanthus, and less frequently, Marsupella emarginata or Jungermannia
atrovirens), acrocarpous mosses (most notably Racomitrium aciculare, plus smaller
quantities of marginal species, such as Philonotis fontana and Dicranella palustris,
Fissidens crassipes and F. rufulus), thallose liverworts (Pellia epiphylla), and small
macroalgae, including Lemanea, Oscillatoria and Mougeotia spp. These taxa occur
against a backdrop of extensive growths of a range of pleurocarpous mosses, including
Rhynchostegium riparioides, Fontinalis squamosa, F. antipyretica, Hygrophypnum
ochraceum (and occasionally H. luridum), Brachythecium rivulare, B. plumosum,
Hyocomium armoricum, Thamnobryum alopecurum and Amblystegium fluviatile.
Vascular plants are likely to be restricted to Callitriche hamulata, plus occasional
marginal growth of species such Glyceria fluitans, Phalaris arundinacea and
Ranunculus flammula. The latter often occurs alongside a range of mire forming
species, of which the mosses Sphagnum, Mnium hornum, Philonotis caespitosa and
Plagiomnium undulatum are most characteristic. This is an assemblage of small,
shallow, turbulent, flashy, neutral to base-poor, oligotrophic, upland rivers, with a
cobble and boulder substrate, often with extensive shading by deciduous trees. Several
of these species persist in the lowest quality sites, most notably Fontinalis antipyretica
and Rhynchostegium riparioides, but most bryophytes are replaced by Amblystegium
riparium. Channel margins are likely to feature more extensive growth of Phalaris
arundinacea, plus Sparganium erectum and a range of smaller amphibious species,
such as Agrostis stolonifera, Glyceria fluitans, Veronica beccabunga and Myosotis
scorpioides. The cover of instream vascular species is generally small, but may include
Callitriche hamulata, Ranunculus peltatus, Elodea nuttallii, Potamogeton crispus,
Sparganium emersum and Ceratophyllum demersum. Larger green filamentous algae
are generally present and will include Cladophora glomerata and Vaucheria spp. This
reflects a shift to more stable, moderate to slow flowing, fertile conditions with reduced
shading of the margins and mixed sand-gravel substrates. This change is therefore
most likely to be associated with a combination of pollution and siltation from diffuse
sources, flow regulation, channel realignment and overgrazing.
65
Chapter 3: Establishing common grounds in European macrophyte assessment for rivers
High quality R-C4x2 streams are dominated by two species Fontinalis antipyretica and
Sparganium emersum, each of which account for 10 percent of the total plant cover.
Other common and widely distributed instream aquatics include Nuphar lutea, Elodea
canadensis and Amblystegium riparium, plus the red encrusting alga Hildenbrandia,
which is highly characteristic of high status R-C4x2 rivers. A diverse range of
pondweed species (especially Potamogeton alpinus, P. perfoliatus and P. natans, but
occasionally P. praelongus or P. gramineus) occur alongside batrachids, such as
Ranunculus fluitans and R. aquatilis, plus Myriophyllum spicatum and Callitriche
hamulata. Marginal vegetation is dominated by Phalaris arundinacea and Sparganium
erectum, but other stand forming species are also frequently present and will include
Scirpus lacustris, Iris pseudacorus, Glyceria aquatica and Equisetum fluviatile. Of the
smaller marginal species Mentha aquatica, Veronica anagallis-aquatica, Alisma
plantago-aquatica, Glyceria fluitans, Berula erecta and Myosotis scorpoides are
especially well represented, and may harbour small patches of various lemnids. Within
the marginal zone Carex rostrata and Lysimachia thyrsiflora are uncommon but are
unique to high status sites. This is an assemblage of medium sized, active, moderate
to fast-flowing, shallow lowland rivers on neutral to base-rich geology with clear,
mesotrophic to eutrophic water. A diversity of substrates occurs, and will include a mix
of sand, gravel and unsilted coarser material. The vegetation itself is a major architect
of hydromorphological diversity. Remnants of this vegetation occur in rivers in central
and north west Europe (e.g. Wiegleb, 1984; Holmes et al., 1999), but it is only in the
less densely populated countries of north east Europe that this vegetation can still be
found with any regularity (e.g. Paal & Trei, 2004, Baattrup-Pedersen et al, 2008). The
most degraded sites are strongly characterised by Potamogeton pectinatus, which
accounts for 21 percent of the total plant cover in common poor or bad status sites. Of
the commoner instream associates Fontinalis antipyretica, Elodea canadensis and
Sparganium emersum are all greatly reduced compared to their contribution in high
status sites, and are likely to be replaced by Potamogeton crispus, Elodea nuttallii,
Lemna minor, Ranunculus penicillatus, Ceratophyllum demersum, Persicaria amphibia
or Zannichellia palustris, plus various large green filamentous algae, including
Cladophora, Rhizoclonium, Vaucheria and Oedogonium. The status of Nuphar lutea
and Amblystegium riparium is little changed in comparison to the highest status sites.
The margins remain dominated by Phalaris arundinacea and Sparganium erectum with
Glyceria aquatica and Scirpus lacustris as common associates. However, in place of a
66
Chapter 3: Establishing common grounds in European macrophyte assessment for rivers
range of smaller herbaceous species Solanum dulcamara, Rorippa amphibia,
Sagittaria sagittifolia or Typha latifolia normally occur. Collectively this assemblage
indicates a highly enriched, stable, sluggish, well lit environment dominated by fine
sediment. Such vegetation is often associated with streams in urban or intensely
agricultural catchments, where management and physical modification of channels and
their margins are the norm.
3.4.2 Development of a common metric for intercalibration
The mICM proves to be a suitable common metric for the intercalibration of the national
macrophyte methods used in this study. Except for two cases all regressions are
characterized by a coefficient of determination ≥ 0.5, thus meeting an important
intercalibration criterion given by Owen et al. (2010) in the comparison of benthic
invertebrate methods. On average, the mICM is related more strongly to the national
methods than the common metric proposed in Chapter 2. However, compared to the
outcomes of a diatom intercalibration exercise its performance is poorer (Kelly et al.,
2008). This is mainly attributable to the low average relation of the mICM to the
Flemish and German methods, underlining their conceptual difference.
This approach to developing a common metric for intercalibration allows differences
between methods to be detected at the level of national indicator lists. The mICM taxa
scores actually represent a correlation with averaged national indicator ratings. Positive
scoring taxa are common indicators of near-natural conditions, negative scoring taxa
generally characterize poor or bad quality. Taxa with low correlation to the mean index
are either indicative of moderate conditions or rated inconsistently among countries.
Obvious discrepancies between the mICM indicator values and the national ratings are
easily identified and adjusted. This option provides the opportunity to harmonize the
national methods by implementing only minor, thus easily justified changes, rather than
seeking wholesale changes in class boundaries which may be politically difficult to
achieve.
The mICM indicator scores were derived by Spearman rank correlation. In selecting
this analysis I assumed that a linear model best describes the distribution of taxa
abundance across the gradient represented by the mean index range. Though not
further explored in this chapter I also tested if a unimodal approach using weighted
averaging of taxa abundances is more suitable to derive indicator scores. Due to lower
67
Chapter 3: Establishing common grounds in European macrophyte assessment for rivers
correlations of the mICM with the national assessment methods this option was
rejected. The linear model seems to better reflect the similarity among national
sensitivity metrics that abundant indicator taxa contribute proportionally more to the
national EQR score.
I also dismissed alternative approaches based on relative macrophyte abundance data
or the exclusion of taxa occurring in less than five surveys since both options also
showed weaker relationships. All national metrics use absolute instead of relative
abundance values. The indicator scores assigned to rare taxa may be biased by their
low occurrence. It is possible that their scores would change when using a larger
dataset. However, the better correlation of the mICM in its proposed version justifies
the inclusion of rare indicator taxa.
A common value of ~0.8 at the 5th percentile of the mICM EQR provides some
reassurance over the potential utility of this approach and demonstrates that there is
sufficient commonality in interpretation of high status within each river type for this view
to form a robust basis for testing national classifications. A 5th percentile of EQR of ~0.8
is consistent with reference site EQR variability in invertebrate based classification
tools, such as RIVPACS (Clarke et al., 1996). It also lends itself to a statistically-based
placement of class boundaries from high-good, down to poor-bad, at unit intervals of
0.2.
Growth form metrics add a new dimension to macrophyte based classification which
departs strongly from structural assessments in which the indicator value of individual
taxa takes priority. Thus, species which share the same growth form may have very
different indicator values (and will thus tend to have different mICM scores), while other
species representing different growth forms may have similar indicator values. Further
work is required to determine how best to integrate elements of national classification
methods not shared by other countries within the approach presented here. Thiebaut et
al. (2002) reported that the performance of diversity based measures was generally
inferior to trophic indices for use in macrophyte classification of rivers. However, Willby
et al. (2008) argued that some form of diversity index was desirable within classification
in order to differentiate between results based on data of contrasting biological quality,
and also to better reflect physical habitat heterogeneity.
68
Chapter 3: Establishing common grounds in European macrophyte assessment for rivers
3.5 Conclusions
This study represents an important contribution to the intercalibration of river
macrophyte classifications in Europe. It defines common reference conditions for three
widespread stream types and provides a means to compare the good ecological status
of national methods. Furthermore, this work offers a general approach to harmonize
the national assessment methods for biological elements of any water category. Based
on the differing national assessments of similar transnational ecotypes the approach
reveals the common ground of national quality classifications. Basic elements are the
common high status sites and the mICM indicator list.
The description of the ecotype-specific communities and their environmental conditions
goes beyond these outcomes. It amalgamates the national notions of biological
communities at high and bad quality status and establishes an international guiding
image that is not influenced by national specialities or biogeographical differences. This
image will be of crucial importance in the follow-up process towards harmonization of
ecological quality classification.
69
Chapter 4: A new procedure for comparing class boundaries of biological assessment methods
70
4 A new procedure for comparing class boundaries of biological assessment methods: a case study from the Danube Basin
4.1 Introduction
Monitoring the biological quality of rivers has a long tradition in the Danube River
Basin. In communist times the evaluation of saprobic water quality was standardized in
Eastern Europe (Helešic, 2006) and several countries supported research on
bioassessment and monitoring (e.g. Zelinka & Marvan, 1961; Rothschein, 1962;
Sládeček, 1973; Uzunov, 1979). However, compared to chemical water classification
biological assessment played a minor role also in the pan-European context (Newman,
1988). Against this background, the European Water Framework Directive 2000/60/EC
(WFD) has set new requirements for water policy. Besides integrated and coordinated
river basin management for all European river systems it stipulates ecological quality
assessment against near-natural reference conditions specific to each type of water
body. For rivers, fish, benthic invertebrates, macrophytes and benthic algae, and
phytoplankton are assessed. Results are given in relation to the near-natural reference
conditions, thus expressed as numbers between 0 (worst status) and 1 (near-natural
reference status), i.e. the ‘Ecological Quality Ratio’ (EQR). The EQR range is split into
five classes (high, good, moderate, poor, and bad).
Although individual countries are in charge of modifying their national assessment
methods or of developing new methods, the quality classification at the European level
is harmonized by intercalibration (Heiskanen et al., 2004). Intercalibration is a legally
binding requirement of the WFD. It guarantees the consistent quality classifications
despite still diverse assessment methods that countries are applying. European
Member States are obliged to compare the results of assessments among countries
that share common water body types in similar biogeographical regions. For this,
countries are organized in so-called Geographical Intercalibration Groups (GIG). A
major policy objective is to achieve good surface water status throughout Europe by
2015. Intercalibration therefore focuses on the EQR values that define good ecological
status, i.e. the high-good and good-moderate class boundaries. A list of the main terms
and definitions connected with the intercalibration process as meant in this chapter is
given in Table 27.
Chapter 4: A new procedure for comparing class boundaries of biological assessment methods
There are three methodological options for intercalibration (European Communities,
2005):
Option 1. Boundaries are compared directly between countries that are using identical
assessment methods (e.g. CB GIG Lakes, 2008).
Option 2. The results of national assessment methods are translated into a comparable
format using common metrics (e.g. Buffagni et al., 2006). Unlike national methods,
common metrics are not optimised for quality assessment but are conversion tools for
biological assessment indices.
Option 3. Different national methods are compared directly by assessing the same
sampling sites using the participating countries national assessment methods (e.g.
Borja et al., 2007; see also Chapter 1 of this thesis).
All these options require data on sites covering the whole range of quality classes to
secure statistical robustness of intercalibration results.
Table 27: Definition of main terms dealt with in this chapter
Main term Definition
1. Intercalibration Process by which European countries compare and harmonize the quality class boundaries of their biological assessment methods (high-good and good-moderate boundary).
2. Harmonization If the comparison of biological assessment methods reveals differences between national class boundaries, these differences are harmonized. This is done by adjusting the national boundaries with reference to biological benchmarks.
3. Biological benchmark Condition of the biological community that represents the transnational reference point for harmonization. The biological benchmark is defined for selected aspects of the biological community measured by common metrics.
4. Common metric A biological metric widely applicable within a GIG or across GIGs, which can be used to derive comparable information among different countries/stream types (Buffagni et al., 2007).
5. Standardization Normalization of metric values via transformation to unitless scores. Metrics are divided by the values representing the near-natural condition or the biological benchmark condition.
6. Threshold value
Value of selected environmental parameters/common metrics that influence/indicate the biological condition at the stream site, e.g. conductivity or agricultural land use in the catchment. Threshold values were used to screen for stream sites of at least good environmental status.
In Central Europe, Member States recently intercalibrated river diatom and invertebrate
classifications by common metrics (Option 2) (CB GIG Rivers, 2008). These metrics
were correlated with the national assessment methods and regression analyses
71
Chapter 4: A new procedure for comparing class boundaries of biological assessment methods
inferred the values of the common metrics that corresponded to the national quality
class boundaries. To compare common metrics between countries they had to be
standardized. For this purpose the participating countries provided data on undisturbed
reference sites, which were selected with harmonized criteria (CB GIG Rivers, 2008).
The biological community of these undisturbed sites yielded the reference value of the
common metrics and provided EQR scales that were comparable between countries.
The principal problem with this approach was the scarcity of reference sites, since
unimpacted conditions no longer exist (e.g. Birk et al., 2007b; Gabriels, 2007) or data
were not available as monitoring focuses on impacted sites. Several countries could
therefore not intercalibrate their methods, especially those applied for large rivers.
Therefore, the question arises: Does intercalibration of class boundaries necessarily
require data on reference sites or are there alternative approaches?
In this study, I developed a new method for river types of five countries in the Danube
River Basin (Figure 7), for which reference data were almost completely unavailable.
Benchmarks were therefore established with data from similarly impacted river sites.
This approach was tested for both, assessment methods based on benthic diatoms
and methods based on benthic invertebrates.
Figure 7: Map of Europe showing the locations of Austria (AT), Slovak Republic (SK), Hungary (HU), Romania (RO) and Bulgaria (BG).
72
Chapter 4: A new procedure for comparing class boundaries of biological assessment methods
4.2 Materials and Methods
4.2.1 National assessment methods and intercalibration common stream types
I intercalibrated two multimetric diatom indices used in Austria and the Slovak Republic
(Table 28). The Austrian method classifies the EQRs of the Trophic Index (TI) (Rott et
al., 1999) and Saprobic Index (SI) (Rott et al., 1997) separately and the overall quality
status is determined by that index delivering the worst result. The Slovak method
integrates the results of three diatom metrics (Indice de Polluosensibilité Spécifique
(IPS): CEMAGREF, 1982; Eutrophication/Pollution Index - Diatom-based (EPI-D):
Dell’Uomo, 1996; Diatom Index by Descy & Coste (1991) (CEE)). The absolute index
values are classified by a five-fold, stream-type specific classification scheme. The
overall status is expressed as the averaged class values of each index divided by the
maximum obtainable score.
Five invertebrate methods were intercalibrated (Table 28). The multimetric indices of
Austria and the Slovak Republic appraise various aspects of the river invertebrate
community such as faunal composition, abundance, richness, diversity, sensitivity and
ecosystem function (BMLFUW, 2006b). The Bulgarian and Hungarian methods
integrate information on taxonomic composition and tolerance to general disturbance,
while the Romanian method is a modification of the Saprobic Index. The Saprobic
Index indicates biodegradable organic pollution on the basis of species composition
and species-specific saprobic indicator values. Further details on these methods are
given by Birk & Schmedtje (2005).
Table 28: National assessment methods for rivers using benthic diatoms and invertebrates.
Country Method name Benthic diatoms Austria Austrian Phytobenthos Assessment - Component: diatoms Slovak Republic Slovak Phytobenthos Assessment - Component: diatoms Benthic invertebrates Austria Austrian System for Ecological River Status Assessment using Benthic Invertebrates Bulgaria Bulgarian Biotic Index for River Quality Assessment (Q-Scheme) Hungary Hungarian Average Score Per Taxon (ASPT) Romania Romanian Saprobic Index following Pantle & Buck (1955) Slovak Republic Slovak System for Ecological River Status Assessment using Benthic Invertebrates
Four common stream types (ECOSTAT, 2004b) (Table 29) were defined for the
intercalibration of the selected assessment methods. Ecoregion, catchment area,
altitude, geology and dominant channel substrate were used to define the stream
73
Chapter 4: A new procedure for comparing class boundaries of biological assessment methods
types. The common types covered small to medium sized, mid-altitude streams of the
Carpathians with coarse bed substrate (Romania and the Slovak Republic), and rivers
of different size and altitude ranges in the Hungarian Plains and the Pontic Province
(Austria, Bulgaria, Hungary, Romania and the Slovak Republic).
Table 29: Common stream types addressed in this study
Stream type abbreviation Common stream type
Ecoregion (Illies, 1967)
Catchment area [km2] Altitude [m] Geology
Channel substrate
R-E1 Carpathians: small to medium, mid-altitude
10 (The Carpathians)
10 - 1000 500 - 800 Siliceous Gravel and boulder
R-E2 Plains: medium-sized, lowland
11 (Hungarian Lowlands) and 12 (Pontic Province)
100 - 1000 < 200 Mixed Sand and silt
R-E3 Plains: large and very large, lowland
11 (Hungarian Lowlands) and 12 (Pontic Province)
> 1000 < 200 Mixed Sand, silt and gravel
R-E4 Plains: medium-sized, mid-altitude
11 (Hungarian Lowlands) and 12 (Pontic Province)
100 - 1000 200 - 500 Mixed Sand and gravel
4.2.2 Data
The analyses were based on national monitoring data from sampling sites at the
common stream types. The data included information on composition and abundance
of benthic diatoms and invertebrates, selected chemical parameters, the classification
of hydromorphological quality (only for invertebrate sampling sites) and catchment land
use.
The number of countries included in the intercalibration for the individual stream types
varied, depending on the relevance of the type to the country, the availability of national
assessment methods and data. The number of sites and samples included into the
analysis differed between countries and stream types. In total, data from 356 sampling
sites were included, comprising 140 diatom and 543 invertebrate samples (Table 30).
The procedures for sampling benthic diatoms for both compared methods was in line
with the European standard EN 13946:2003 or related national protocols. The
invertebrate samples were obtained by country-specific, national sampling protocols.
Two groups of sampling methods were used (Table 31): Pro-rata Multi-Habitat
Sampling (Hering et al., 2003) and Standard Handnet Sampling (EN 27828:1994). The
74
Chapter 4: A new procedure for comparing class boundaries of biological assessment methods
main differences were area-related versus time-related sampling in the field, and, in
case of the Multi-Habitat Sampling, the application of sub-sampling procedures in the
laboratory. Differences between country-specific methods related to mesh size,
recording of abundance and the level of taxonomic identification.
Table 30: The number of sites and samples per country and common intercalibration type, and number of taxa per sample
Number of taxa per sample Stream type abbreviation Country Number of sites
Number of samples median min / max
Benthic diatoms
Austria 81 117 30 6 / 83 R-E4 Slovak
Republic 10 23 38 16 / 75
Benthic invertebrates Romania 52 142 14 2 / 63
R-E1 Slovak Republic 39 103 46 1 / 83
Romania 24 41 10 2 / 31 R-E2 Slovak
Republic 11 23 28 6 / 48
R-E3 Bulgaria 32 63 14 3 / 28
Austria 46 58 61.5 10 / 105 Hungary 43 76 13.5 1 / 68 R-E4 Slovak
Republic 18 37 25 3 / 57
Table 31: National methods for sampling and processing invertebrate samples
Sampling method Pro-rata multi-habitat-sampling Standard-handnet-sampling Country Austria, Slovak Republic, Hungary Bulgaria, Romania
Description
Area-related sampling using handnet (20 sampling units taken from all habitat types with >=5% coverage; Hungary: 10 samples)
Time-related using handnet (3 to 5 min., all available habitats)
Mesh size 500 µm Hungary: 950 µm 500 µm
Sampling technique Kick and sweep Kick and sweep, additional hand picking
Abundance recording Individuals per m2 Bulgaria: 5 abundance classes Romania: number of individuals
Sub-sampling Yes No
Identification level Species Bulgaria: genus and family Romania: species
Reference Hering et al. (2003) Nieuwenhuis (2005) EN 27 828:1994
75
Chapter 4: A new procedure for comparing class boundaries of biological assessment methods
Table 32 lists the environmental data collected for each sampling site. Physico-
chemical parameters were generally measured monthly and averaged over six months
(diatom sampling sites) or one year (invertebrate sampling sites).
Table 32: Environmental data collected at each sampling site
Physico-chemical parameters Conductivity, pH, alkalinity, dissolved oxygen, oxygen saturation, biological oxygen demand (5 day), total phosphorus, ortho-phosphate, nitrate, nitrite, ammonium Hydromorphological parameter Hydromorphological quality status (see Table 33) Catchment land use parameters % Urban land use % Intensive agriculture % Non-intensive agriculture % Forest Land use index (Böhmer et al. 2004)
Since no common method for evaluating the structural quality of sites was available, I
developed a classification scheme to assess the hydromorphological status of the
invertebrate sampling sites. According to the degree of degradation one of three
classes was allocated to each site (Table 33). This classification was based on expert
judgement of the field staff who sampled the streams.
Share of urban land cover (Corine Land Cover (CLC) class 1), intensive agricultural
land cover (CLC codes 2.1, 2.2, 2.4.1, 2.4.2) and non-intensive agricultural land cover
(CLC codes 2.3.1, 2.4.3, 2.4.4) in the catchment were taken from CLC data (Bossard et
al., 2000). These data were used to calculate the Land Use Index (Böhmer et al.,
2004): 4 * urban land use + 2 * intensive agriculture + non-intensive agriculture.
Environmental data were not available for some Romanian and Slovakian sites.
4.2.3 Data analysis
Overview
Figure 8 provides an overview of the analytical procedure. The intercalibration
approach was based on the application of common metrics. Using environmental
criteria I screened for sampling sites of at least good environmental status. For these
sites the distribution of common metric values was calculated. The upper or lower
quartile values of this distribution were used as the “biological benchmark”.
76
Chapter 4: A new procedure for comparing class boundaries of biological assessment methods
Table 33: Classification scheme to assess the hydromorphological quality status of invertebrate sampling sites
Class 1 - near-natural hydromorphological conditions
- Stream type specific variability of channel depth and channel width, shallow profile, close connectivity of the stream and the floodplain
- Natural channel substrate conditions (composition and variability), presence of dead wood - Bank profile and bank structure unmodified - Presence of natural riparian vegetation - Natural hydromorphological dynamic is maintained - Low degree of anthropogenic land use in the floodplain Class 2 - moderately altered hydromorphological conditions - Decreased variability of channel depth and channel width - Minor changes to bank morphologies, or only one bank is fixed with "soft works" - Riparian vegetation altered - Loss of stream length, longitudinal profile is altered by man Class 3 – severely altered hydromorphological conditions - Obvious presence of hard engineering - Severe modifications of instream structures, bed and bank fixation and artificial substrates - No or only minor variability of channel substrate - No riparian zone between river and land use - Channelised, straightened and/or deep-cut river - Disconnection of river and floodplain
In the next step, I regressed common metrics against national assessment indices; this
was done differently for diatom and invertebrate methods:
(1) For comparing the boundaries of diatom methods the national indices represented
the predictor variables. Here, I identified the common metric values corresponding to
the national good quality boundaries.
(2) For setting the boundaries of invertebrate methods the reverse approach was
applied. The common metrics were used as predictor variables from which national
boundaries were inferred. I applied this different approach because for only two of the
five national methods ecological quality classes were defined.
Selection of common metrics
The results of the national assessment methods were compared against common
methods, the so-called “Intercalibration Common Multimetric indices” (ICMi, Buffagni et
al., 2005). These indices represented combinations of two or more single metrics that
measured different aspects of the biological community. The diatom ICMi comprised
the common metrics IPS (CEMAGREF, 1982) and TI (Rott et al., 1999) which are parts
77
Chapter 4: A new procedure for comparing class boundaries of biological assessment methods
of the national assessment methods of Austria and the Slovak Republic, respectively.
Kelly et al. (2008) applied this multimetric index to compare the diatom indices of
Central European countries.
Figure 8: Overview of the analytical procedure
For the invertebrate methods, I developed an invertebrate ICMi using the biological
data collated in this study. 140 metrics at the taxonomic level of family were correlated
with national indices. Twelve common metrics were selected, which represent different
metric types (Hering et al., 2006b) and were among those indices correlating most
78
Chapter 4: A new procedure for comparing class boundaries of biological assessment methods
strongly with all the national indices (average Spearman Rank correlation coefficient
> 0.55). Out of these, metrics of different type were combined into four different
multimetric indices assessing taxonomical composition, abundance, diversity and
sensitivity. The multimetric index that correlated best with all the national indices was
used as the invertebrate ICMi.
Data screening
I identified sites of at least good status based on threshold values of selected
environmental parameters. These values were mainly taken from scientific literature
and environmental standards (Table 34). In the discussion section, I describe the
rationale for their selection in detail.
Table 34: Threshold values of environmental parameters used to screen for diatom (DI, only type R-E4) and invertebrate (BI) sampling sites of high or good environmental status (n.a. =
not applicable).
Common intercalibration type Carpathians: R-E1 Plains: R-E2, R-E3, R-E4 Threshold for High environmental status Good environmental status Biological quality element BI DI BI Biological parameter Average Score Per Taxon ≥ 6.4 n.a. ≥ 5.1 Chemical parameters Total phosphorus [µg l-1] n.a. < 100 n.a. Ortho-phosphate [µg l-1] n.a. < 70 n.a. Biological oxygen demand (5 day) [mg l-1] ≤ 2.5 n.a. ≤ 5.0 Conductivity [µS cm-1] n.a. < 1000 Hydromorphological parameter Quality class 1 n.a. 1 and 2 Land use parameter Land use index ≤ 50 ≤ 140
For diatoms, I specified limits for total phosphorus, orthophosphate, conductivity and
Land Use Index (Table 34). Good environmental status was allocated to every site that
showed values below these limits. The invertebrate sampling sites were classified by
biotic criteria and environmental data. The biological classification was based on the
quality class boundaries of the Austrian Saprobic Index (ÖNORM M6232:1997)
proposed for mountain and lowland rivers in the Danube River Basin by Knoben et al.
(1999). These boundaries were translated into an index on family level (Average Score
Per Taxon, ASPT; Armitage et al., 1983) by linear regression. First, sites were
screened by their samples’ mean ASPT, and then the abiotic criteria were applied to
79
Chapter 4: A new procedure for comparing class boundaries of biological assessment methods
those sites that passed the ASPT threshold. Different criteria were established for the
river types of the Carpathians and the Plains. Data sets of small to medium sized
streams in the Carpathian Mountains (R-E1) were screened to identify sites of high
environmental status. Data from sites of high status were generally scarce for the
common types in the Plains (R-E2, R-E3 and R-E4). Here, I used adapted threshold
values to identify sampling sites of good environmental status.
Definition and application of benchmarks
For the purpose of this analysis, “biological benchmarks” are defined as values of the
common metrics that correspond to similar levels of disturbance, representing either
the high-good or the good-moderate boundary.
Biological benchmarks were derived from the data of sites of at least good
environmental status. I calculated the common metrics for all sites and identified the
distribution of common metric values that occurred at high or good status sites,
respectively. Out of this distribution I selected the quartile values to define biological
benchmarks. For the intercalibration of diatom assessment methods I chose the upper
quartile for IPS and the lower quartile for TI as benchmarks. Basis was the metric
distribution of the combined Austrian and Slovak data, since diatom data were derived
by identical sampling protocols. For the invertebrate metrics, the lower quartiles were
selected, since metric values increase with degradation. Benchmark calculation was
done separately per country and stream type to account for the different national
sampling protocols. Standardized common metrics were then combined to the
invertebrate ICMi by averaging.
The relation of national diatom indices and the diatom ICMi was calculated by
regression models. The quality boundaries high-good and good-moderate of the
Austrian and Slovak assessment methods were translated into corresponding values of
the ICMi. In invertebrate intercalibration the ICMi was used to harmonize the national
quality class boundaries. Depending on the screened dataset, an ICMi value of ‘1’
represented either the high-good or the good-moderate boundary. Based on the
relationship of ICMi and national index the national boundaries were inferred by
regression analysis. Those boundaries that were not specified by the screened dataset
were defined as the 20 percent deviation from the modelled boundaries.
80
Chapter 4: A new procedure for comparing class boundaries of biological assessment methods
4.3 Results
4.3.1 Selection of common metrics
The ICMi for the intercalibration of the invertebrate methods comprised four metrics:
Average Score Per Taxon (ASPT), Austrian Structure Index at Family Level (Structure
Index), Total Number of Families (#fam) and Relative abundance of Ephemeroptera,
Plecoptera and Trichoptera taxa (%EPT). Type-specific analyses of common metrics
and national assessment indices resulted in mean correlation coefficients ranging from
R = 0.56 (%EPT) to R = 0.73 (ASPT). The ICMi and its component metrics correlated
significantly with catchment land use, hydromorphological status, dissolved oxygen
concentration and biological oxygen demand (Table 35). The correlation coefficients of
ICMi and national indices varied between R = 0.67 and R = 0.81.
Table 35: Maximum Spearman Rank correlation coefficients for environmental variables and common metrics from national datasets (n.s. = non-significant correlation; *p<0.05, **p<0.01, ***p<0.001).
Environmental parameter #fam ASPT Structure Index %EPT EE ICMi
Land use index n.s. -0.63*** -0.55*** -0.40* -0.48***
Hydromorphological quality class -0.42* n.s. -0.57*** -0.71* -0.75*
Dissolved oxygen concentration 0.74*** 0.72*** 0.62** 0.41* 0.49**
Biological oxygen demand -0.51* -0.59* -0.51* -0.53* -0.62**
Correlation coefficients for national indices against the diatom ICMi were generally
higher (R ≥ 0.89). The individual metrics TI and IPS showed highly significant
relationships with all of the environmental parameters except temperature, pH, oxygen
concentration (only TI) and oxidised nitrogen.
4.3.2 Data screening
27 sites passed the diatom screening thresholds of good environmental status. Total
phosphorus represented the most stringent criterion that classified sites as “moderate”
or worse. The screening procedure using the harmonized quality criteria for
invertebrates resulted in national data subsets of different size. On average, national
datasets comprised seven sites of at least good environmental status.
81
Chapter 4: A new procedure for comparing class boundaries of biological assessment methods
4.3.3 Definition and application of benchmarks
The benchmarks calculated for diatom metrics were IPS = 16.9 (upper quartile value)
and TI = 2.44 (lower quartile value). The invertebrate common metrics gave different
quartile values for the individual type/country datasets. High status samples of the
mountain streams, for instance, showed a quartile value of 9 families (Romania) and 24
families (Slovakia). Another example is the percentage of EPT families in R-E4
samples of good environmental status: 10 percent for Austria versus 50 percent for
Hungary. In Figure 9, the ranges of common metrics are juxtaposed for selected data
subsets.
I used linear models to translate the national diatom boundaries into diatom ICMi
values (Figure 10). For the Austrian method, the overall biological quality class is
determined by the worst of the individual module classes. Therefore, the more
precautionary boundary values of the Trophic Index (Table 36) were compared to the
Slovak quality boundaries. The comparison revealed different settings for the high-
good boundary and the near-natural reference value between countries.
Table 36: Quality class boundaries and near-natural reference values of the national diatom indices translated into diatom ICMi values (dICMi = diatom ICMi; TI-AT = Austrian Trophic
Index; SI-AT = Austrian Saprobic Index; DI-SK = Slovak Diatom-Index; 95CI = 95 percent confidence interval of regression line).
Class boundary TI-AT dICMi 95CI SI-AT dICMi 95CI DI-SK dICMi 95CI High-good 0.69 1.00 ±0.02 0.85 0.90 ±0.02 0.90 0.89 ±0.02 Good-moderate 0.41 0.68 ±0.01 0.71 0.68 ±0.02 0.70 0.67 ±0.02 Near-natural reference 1.00 1.35 ±0.03 1.00 1.15 ±0.04 1.00 0.99 ±0.03
The boundaries for the national invertebrate methods were predicted using linear or
lognormal regression against the invertebrate ICMi (see Figure 11 for an example).
Table 37 shows the boundaries for national assessment methods derived from the
comparison to the ICMi. In addition, the table indicates those values that were defined
by 20 percent deviation from predicted boundaries.
82
Chapter 4: A new procedure for comparing class boundaries of biological assessment methods
Figure 9: Calculation of benchmarks. Distribution of diatom (a, b) and invertebrate (c to f) common metric values at sites of good (A) or high (A*, Slovak R-E1) and worse (B) environmental status. Metrics were standardized by the quartile values marked with an arrow.
Relevant quartiles between groups (A - B) are significantly different at p<0.001 (χ2-Test).
83
Chapter 4: A new procedure for comparing class boundaries of biological assessment methods
Figure 10: Boundary comparison. Translation of Austrian (TI-AT) and Slovak (DI-SK) good quality boundaries into comparable values of the diatom common metric (dICMi) by linear regression (dashed lines). White squares represent samples of good environmental status.
Figure 11: Setting the high-good class boundary for the Slovak invertebrate index (MMI-SK) using the biological benchmark (invertebrate ICMi = 1). White squares represent samples of high environmental status (R2 = coefficient of determination).
84
Chapter 4: A new procedure for comparing class boundaries of biological assessment methods
85
Table 37: Biological class boundaries derived from regression analysis of the invertebrate ICMi against national indices (95CI = 95 percent confidence interval of regression line; * = class
boundary defined as 20 percent deviation from predicted boundary value; ‡ = Confidence interval derived from regression analysis using ranks transformed into whole numbers (“1” = 1, “1 to 2” = 2, “2” = 3 etc.).
IC type Country Class boundary Boundary value 95CI High-good 1.70
Romania Good-moderate 2.27*
± 0.09
High-good 0.74 R-E1
Slovak Republic Good-moderate 0.54*
± 0.02
High-good 1.81* Romania
Good-moderate 2.26 ± 0.09
High-good 0.74* R-E2
Slovak Republic Good-moderate 0.54
± 0.05
High-good 4 to 5* R-E3 Bulgaria
Good-moderate 3 to 4 ± 0.39‡
High-good 0.79* Austria
Good-moderate 0.59 ± 0.03
High-good 7.36* Hungary
Good-moderate 5.52 ± 0.14
High-good 0.72*
R-E4
Slovak Republic Good-moderate 0.52
± 0.04
4.4 Discussion
4.4.1 Objectives of boundary comparison and setting
The application of benchmarks for comparing and setting boundaries follows different
objectives. In boundary comparison, discrepancies between national classifications are
identified, but no guidance is given for adjustment. For instance, in this analysis the
diatom intercalibration revealed differing high-good boundaries and reference values
between the Austrian and Slovak classifications. In the official intercalibration exercise
of the Central-Baltic GIG harmonization was achieved in such cases by averaging the
boundary values of all participating countries (CB GIG Rivers, 2008). This approach
has the character of a committee agreement and is inappropriate if only a small
number of national methods are involved. However, with reference to the benchmark,
the standardized common metric indicates harmonization requirements: only the high-
good boundary of the Austrian Trophic Index is close to a dICMi value of ‘1’. This
suggests that a boundary adjustment of the other indices is needed.
Chapter 4: A new procedure for comparing class boundaries of biological assessment methods
In contrast, benchmarks used in boundary setting establish harmonized biological
standards directly, without reference to existing national classifications. A somewhat
similar approach was described by Sandin & Hering (2004) who applied abiotic
descriptors of organic pollution for setting boundaries for invertebrate assessment
indices. However, the parameter thresholds were derived from existing national
classifications that were actually intercalibrated. Buffagni et al. (2007) proposed an
independent scientific classification of biological data to be used as a benchmark in
intercalibration. In the present study, the boundaries were mainly derived from abiotic
criteria. This concept accounts for the differing status of national method development
in the Danube River Basin (Schmedtje, 2005). The boundary setting approach allows
for a gradual intercalibration exercise. As soon as individual countries have completed
their national assessment methods, the national quality class boundaries can be
adapted to the common benchmark.
4.4.2 Rationale for selecting environmental parameters for benchmark definition
A reasonable definition of thresholds requires distinct pressure-impact relationships
between environmental parameters and intercalibrated biological metrics. I
demonstrated correlations between the environmental parameters and the common
metrics and significant differences between the quartiles of the common metric data in
the screened data sets. The actual threshold values were derived from scientific
literature and environmental standards, and they were confirmed by expert judgement.
Because of their importance in the applied intercalibration procedure I briefly describe
the rationale for selecting the criteria in the following paragraphs.
The abiotic screening criteria are either factors that affect the stream biota directly
(phosphorus concentrations for diatoms; biological oxygen demand, hydromorphology
for invertebrates), or indirect, integrative indicators of various human influences
(conductivity, land use). Their impact on the invertebrate community is considered by
using a biotic index. The Average Score Per Taxon (ASPT) primarily indicates the
effects of organic pollution, but it also responds to hydromorphological degradation
(Buffagni et al., 2005) and other stressor types. The metric is less influenced by
seasonal variation and sampling differences (Armitage et al., 1983; Friberg et al., 2006)
and therefore suited for the analysis of data from different sources. The ASPT
thresholds used for screening sites corresponded to limits for the Saprobic Index that
86
Chapter 4: A new procedure for comparing class boundaries of biological assessment methods
were proposed by Knoben et al. (1999). I translated these values into ASPT to benefit
from the features of a common metric, i.e. minimisation of differences caused by
biogeographical variations, the type of degradation, the level of taxonomic identification
or the sampling method. The defined thresholds fall 3 percent (for high environmental
status in small mountain streams) and 20 percent (for good environmental status in
medium-sized lowland streams) below the values for near-natural reference conditions
used by the British River Invertebrate Prediction and Classification System (Wright et
al., 2000) for small mountain and medium-sized lowland streams, respectively (see
Chapter 1 of this thesis).
The phosphorus thresholds for screening the diatom sites correspond to the good-
moderate boundary values for these parameters applied in Germany (LAWA-AO,
2007). Compared to the Austrian and Slovak standards (Deutsch & Kreuzinger, 2005)
these thresholds are rather precautionary if applied to R-E4 rivers. Sládeček (1973)
gave various examples of the direct relationship between biological oxygen demand
(BOD) and the benthic invertebrate community. The author allocated a BOD of 2.5 mg
l-1 to the lower range of oligosaprobic status, while the beta-mesosaprobic status was
characterised by BOD values of about 5.0 mg l-1. The latter threshold, as well as the
conductivity limit that I used, corresponds to the bottom end of good chemical water
quality in various national and international classification schemes (e.g. Newman,
1988, ICPDR, 2004, MMGA, 2006). Parameters relating to hydromorphological status
comprise overall quality indicators (longitudinal stream profile) and ratings for specific
elements that are relevant to the benthic invertebrates, such as riparian vegetation
(extent and degree of shading), instream woody debris and bank modification (Lorenz
et al., 2004, Feld & Hering, 2007).
Catchment land use generally represents an integrative measure of human influences
on stream ecosystems (Allan, 2004) as it reflects the driving forces impairing river
quality. Agricultural and urban land use account for an array of mechanisms that alter
the riverine environment. Their extent is related to the proportion of particular land use
categories in the catchment. The Land Use Index combines and weights the
percentage cover of different land uses. The threshold value that I selected allows, for
instance, for a maximum of 12.5 percent (high environmental quality) and 35 percent
(good environmental quality) urban land cover in the catchment. However, these
87
Chapter 4: A new procedure for comparing class boundaries of biological assessment methods
numbers are hypothetical because human settlements are usually accompanied by
farmland. Therefore, the actual percentage of urban land cover at threshold is much
lower.
4.4.3 Consistent and verifiable definition of benchmarks
The official WFD intercalibration exercise is a comprehensive procedure covering large
geographical areas and different countries (ECOSTAT, 2004b). If many national
methods have to be intercalibrated, the use of common metrics is scientifically sound
and convenient (Buffagni et al., 2006, 2007). The crucial steps of the intercalibration
analysis are (1) relating national indices to common metrics and (2) standardizing
common metrics using a benchmark. Cross-national comparability of common metric
values can only be achieved after the second step. Like EQRs it establishes a relative
measure (observed condition in relation to benchmark condition) that compensates for
the biogeographical and methodological differences of each national method (Buffagni
et al., 2005). For convenience, both steps can be completed individually by each
country (CB GIG Rivers, 2008).
Because the intercalibration results will influence water management decisions across
Europe, the process must be accountable. In this regard, Biggs (2006) commented that
standardization based on near-natural reference sites is difficult to verify if these
reference sites are identified by the Member States themselves. Following the concept
of “zero or insignificant pressure”, any procedure to screen for pristine sites requires
extensive datasets. European Communities (2003), for instance, specified 19 general
screening criteria. Depending on data availability, only a limited number of criteria can
be checked in practice. The guidelines for selecting reference sites in the Central
European intercalibration exercise dealt with this by accepting gaps in data and
variations in the quality of data to a certain extent (CB GIG Rivers, 2008). Furthermore,
even the criteria defined by European Communities (2003) do not necessarily meet the
definition of ‘undisturbed’ conditions; large rivers, lowland rivers and almost all rivers in
the Mediterranean have been so severely altered by hydraulic engineering, the
disconnection of the rivers and its floodplain, water abstraction, pesticides and a
multitude of other impacts that undisturbed, pristine conditions do not exist any longer
(Moss, 2007). Basing assessment methods and intercalibration on the comparison with
“undisturbed” references is therefore a risky approach, as the actual status is
88
Chapter 4: A new procedure for comparing class boundaries of biological assessment methods
compared to an almost unknown status. Precision and confidence is much higher if
benchmarks are set in a transparent and verifiable way.
The definition of selected environmental criteria described in this contribution offers a
practical solution to problems of data availability that are often encountered in
intercalibration (Buffagni et al., 2007). In this approach, the amount of data required is
comparatively low. Except for hydromorphological quality, I used parameters that were
collected by standard monitoring or satellite remote sensing. The availability of this
data accounted for a complete database that enabled consistent site screening, and
therefore a verifiable standardization process.
89
Summary and conclusions
90
Summary and conclusions
The research presented in this thesis was directed by the question, how the definitions
of good ecological status can best be compared between national assessment
methods. I approached this problem by investigating three related aspects:
1. Relationships between the biological indices
The relationship between the biological indices employed by the national assessment
methods was explored. I found out that invertebrate-based indices were stronger
correlated than those used in macrophyte assessment. The ten national invertebrate-
indices applied to data of two stream types showed an average coefficient of
determination larger than 0.5 (Chapter 1). The four macrophyte-indices were related
with a mean R2 value of less than 0.3 (Chapter 2). Here, nonlinear equations provided
better fits in most of the regressions. In both cases, biological indices of the same type
(indices sensitive to organic pollution or eutrophication) showed best correlation results
(R2 > 0.7).
These outcomes were relevant for selecting the intercalibration approach. The strong
relation of invertebrate-indices allowed for a direct comparison of national assessment
methods. Two common scales were used: (1) The national index showing the highest
mean correlation of all indices. (2) The “Integrative Multimetric Index for
Intercalibration” (IMI-IC), an artificial index designed for the purpose of intercalibration.
This index was defined as the mean of all national index values calculated for a
sample. The average R2 of the IMI-IC amounted to nearly 0.8, with the indices applied
to the data of medium-sized lowland streams performing slightly better. Due to the
weaker relationships between macrophyte-indices, I also tested the performance of
common metrics besides using the best correlated national index. The trophic index
“Ellenberg_N” was considerably related to three out of four assessment methods.
However, the average coefficient of determination was below 0.5 due to the poor
relationship with the Dutch Macrophyte Score.
In Chapter 3, the “macrophyte Intercalibration Common Metric” (mICM) was developed
to compare seven national methods at three Central European stream types. This
common metric yielded a mean R2 value above 0.6, with the correlations of the
mountain type data clearly performing above average (R2 > 0.7). The mICM was based
Summary and conclusions
on a set of stream type-specific, common indicator species. This concept allowed for
amendments of the national indicator lists aiming at harmonized quality classification.
Chapter 4 describes the use of common metrics for the intercalibration of diatom and
invertebrate methods. The diatom methods were strongly related to the common metric
(R2 ≥ 0.8). The Spearman correlation coefficients of the invertebrate methods ranged
between 0.67 and 0.81. The general approach of using common metrics accounted for
the differing status of national method development in the Danube River Basin and
thus provided the basis for a gradual intercalibration exercise. As soon as individual
countries will have completed their national assessment methods, the national quality
class boundaries can be compared via common metrics.
2. Role of reference conditions in the intercalibration exercise
The second aspect of my investigations focused on the role of reference conditions in
the intercalibration exercise. The good ecological status is defined as a slight deviation
from undisturbed conditions. These undisturbed conditions represent the reference
point of assessment. In the intercalibration process a harmonized reference setting is
key to successful boundary comparison. In this thesis, I tested various approaches to
define comparable reference conditions between national methods. High status sites
identified by means of abiotic reference criteria (pre-classification) and biological
validation (post-classification) set common stream type-specific reference values for
the analyses in Chapter 1. The 75th percentile index values at high status sites
established rather stringent conditions compared to the national references. In Chapter
2, the 95th percentile values of the entire data range were set as reference points. This
approach resorted to best available conditions and did not require additional
environmental data. However, this reference setting corresponded to different quality
status according to the national classifications. These outcomes pointed at basic
differences in the national conceptions of the reference state.
To solve these incomparabilities the national definitions of high status had to be
consolidated. In Chapter 3, I described the common stream type-specific macrophyte
communities occurring under undisturbed conditions. This established an international
guiding image that was not influenced by national specialities or biogeographical
differences. Sites classified in high status by the majority of national methods, and by
none of the methods in moderate or worse status, were used to set reference values.
91
Summary and conclusions
The narrow spread of mICM values among these common high status sites provided
some reassurance over the potential utility of this approach and demonstrated that
there is sufficient commonality in interpretation of high status within each stream type
for this view to form a robust basis for testing national classifications.
In the Danube River Basin case study, data from near-natural reference sites were
generally scarce. Therefore, an alternative approach was tested based on sites
impacted by similar levels of disturbance. Using environmental variables I screened for
sampling sites of at least good environmental status. Common metric values obtained
from the screened datasets revealed “biological benchmarks”, that represented
harmonized points of reference for the intercalibration exercise. Unlike in the previous
case studies, the calculation of invertebrate benchmarks was done separately per
country and stream type to account for the different national sampling protocols.
3. Comparison and harmonization of national good status boundaries
The third aspect of my investigations covered the actual comparison and harmonization
of the national boundaries of good ecological status. In particular cases, the boundary
comparisons presented in Chapter 1 revealed discrepancies between national
classification schemes of more than 25 percent. The extent of differences between
class boundaries was largely dependent on the common scale used for comparison.
The use of abiotic pressure data in intercalibration allowed for an additional
interpretation of these results, indicating that harmonization is only required between
two groups of boundaries with overlapping pressure intervals. For the macrophyte
methods both direct and indirect intercalibration options disclosed major differences
between the national good status boundaries. However, the nonlinear relationships of
the macrophyte indices made the comparison difficult. In the lower quality range Mean
Trophic Rank and Ellenberg_N were not responding to changes of the German
Reference Index. The German class boundaries thus showed overlapping confidence
intervals when transferred into the common scale.
The common grounds in European macrophyte assessment established in Chapter 3
did not comprise any comparison of national quality classes. However, the description
of the ecotype-specific communities and their environmental conditions amalgamated
the national notions of biological communities at high and bad quality status.
Furthermore, the 5th percentile of mICM EQR of ~0.8 was consistent with reference site
92
Summary and conclusions
EQR variability in invertebrate based classification tools. It thus lends itself to a
statistically-based placement of class boundaries from high-good, down to poor-bad, at
unit intervals of 0.2. Both guiding image and mICM boundaries will be of crucial
importance in the follow-up process towards harmonization of ecological quality
classification for river macrophytes.
The intercalibration exercise performed in Chapter 4 comprised the comparison and
harmonization of national quality boundaries. The diatom classifications of Austria and
the Slovak Republic were compared using the biological benchmarks. This analysis
revealed different settings for the high-good boundary and the near-natural reference
value between countries. Here, the biological benchmark allowed for the identification
of discrepancies between boundaries, but no guidance was given for their adjustment.
In contrast, the benchmarking approach was used to set the national good quality
boundaries for the invertebrate methods. The benchmarks, that were derived using a
set of abiotic criteria characterizing at least good environmental status, established
harmonized biological standards directly, without reference to existing national
classifications.
Conclusions
The intercalibration exercise plays a prominent role in setting quality standards for
European surface waters. The process establishes a transboundary concept of good
ecological status that is of high socio-economic relevance: European Member States
are obliged to maintain or restore their water bodies to this status. Against this
background it is necessary to critically review validity and limitations of intercalibration.
In this final section I am widening the scope of this dissertation and touch on relevant
aspects excluded from the specific examinations of the main chapters.
The Water Framework Directive literally “frames” the scientific work presented in this
thesis, basically by the ecological assumptions that underlie the design of the Directive
(Steyaert & Ollivier, 2007, Hatton-Ellis, 2008). The concept of classifying ecological
status implies a static, non-dynamic notion of nature. The natural conditions are prized,
and human activities are considered as a source of disturbance responsible for status
degradation. This status is mainly characterized by the taxonomic composition and
abundance of selected organism groups, defining nature in terms of the integrity of the
aquatic communities. These statements set out the main aspects of the ecological
93
Summary and conclusions
perception of the WFD. It is far beyond the scope of this thesis to rate the
appropriateness and suitability of these assumptions. Nevertheless, they form
important preconditions that provide the conceptual basis for ecological status
assessment and intercalibration.
More relevant for the actual evaluation of the intercalibration process is the issue of
uncertainty related to its results. Various studies highlight effects of sampling method
and sample size (Clarke et al., 2006, Vlek et al., 2006), sample processing (Haase et
al., 2006) and temporal variation (Sporka et al., 2006) on the outcomes of river
macrozoobenthos assessments. Carstensen (2007) specifies monitoring requirements
to ensure adequate confidence and precision in classification. However, this is a new,
largely unexplored topic. Therefore, few of the national methods covered in this thesis
employ schemes for error estimation. In the presented intercalibration analyses
uncertainty is only considered in terms of the confidence intervals of the regression
performed between assessment indices. Other works (Kelly et al., 2008, Owen et al.,
2010) use predefined intervals (“harmonization bands”) instead of single boundary
values to account for various indefinite errors in the comparison. Future studies on
intercalibration will have to consider in more detail the role of uncertainty and its effects
on the harmonization of national classifications.
A general criticism of the intercalibration process is raised by Kelly et al. (2008). The
legal requirement to intercalibrate probably contributes to a conservative approach to
method development, since radical approaches to ecological status assessment are,
by their nature, more difficult to compare with other methods. This becomes evident in
the intercalibration of macrophyte classifications. Here, the more innovative growth
form appraisal had to be excluded due to its incomparability with the classical
assessments based on macrophyte composition. Changing land use practices and
industries, but on the other hand measures of the river basin management will reveal
new or unforeseen threats to the aquatic environment. In Germany, for instance, the
relevance of organic pollution has declined over the past decades as more and more
households were connected to sewage treatment and industrial pollution became more
strongly regulated. These measures exposed the severe impacts of diffuse agricultural
pollutants and structural degradation on riverine ecosystems. Today, also pesticides,
organic toxicants or pharmaceuticals threaten the aquatic ecosystems, although their
94
Summary and conclusions
precise impacts are largely unknown. These conditions require a certain flexibility in
quality monitoring, but the intercalibration process may act as an administrative barrier
constraining future adaptability.
My final remark returns to the fundamental issue already raised in the preface: How
can the normative idea of good status be adequately defined by means of scientific
approaches? Pollard & van de Bund (2005) outline theoretical options for the boundary
setting of good quality status, like identification of discontinuities in the biological
response to anthropogenic pressure, or the cross-over of two antagonistic biological
metrics. In practice, these approaches are often unfeasible due to the inability to
identify clear pressure-impact-relationships from regular monitoring data. But in
general, the application of these concepts (e.g. ecological breakpoints, Buffagni et al.,
2004) allows for a more defensible, albeit arbitrary boundary setting: What is justifying
the selection of these specific criteria and not others? The recent discussion on
environmental thresholds (Groffman et al., 2006) provides utilitarian arguments: The
ecosystem quality has significantly declined if ecological services, i.e. specific
ecosystem functions that are valued by humans, are endangered. However, the same
authors question the applicability of this concept since these services are often difficult
to measure.
The experience I gained during the last years allows for a concluding appraisal: How
do I actually rate the intercalibration exercise? Here, I have to give an ambiguous
answer. On the one hand, the pan-European discourse on ecological assessment and
environmental quality standards, that intercalibration initiated, cannot be overrated. The
exercise promoted transboundary collaboration between scientists and water
managers, and already yielded solid outcomes compared to the difficulties the process
had to face. On the other hand, the exercise revealed considerable knowledge gaps,
for instance, with regard to the ecological processes in aquatic systems and their
response to human pressure or restoration. In-depth investigations of these issues
were hampered by the tight schedule of the WFD. In the follow-up of intercalibration it
is necessary to keep the right balance between the legal demands and the scientific
essentials. Moreover, I see the intercalibration work as a continuous requirement within
the overall WFD obligations. Many upcoming challenges like climate change will have
to be addressed on the international level. The established network of practitioners and
95
Summary and conclusions
applied scientists already proved efficient in dealing with the various issues of water
monitoring and ecological assessment. Therefore, I recommend that Member States
ensure to maintain this expert network beyond the currently envisaged time frame.
The thesis at hand contains some of the first studies in support of the WFD
intercalibration exercise. Therefore, it mainly concentrates on approaches to compare
existing classification schemes. Boundary setting was committed to the developers of
the national assessment methods. Future research will have to focus on an objective
rationale for classification that goes beyond committee agreements or expert
consensus. Here, a dialog between ecology and environmental ethics could bring
forward a consolidated notion of good quality that satisfies both the needs of nature
and society. In this regard the intercalibration process holds the potential to pave the
way for an integrated and applicable code of conduct towards the environment.
96
Zusammenfassung
97
Zusammenfassung
Hintergrund
„Was soll ich tun?” lautet nach Kant (1800) eine der Grundfragen der Philosophie,
welche stellvertretend für die vielfältigen Inhalte ethischer Reflexionen steht. Waren
vornehmlich die interpersonellen Beziehungen Gegenstand der Ethik, so fand in der
zweiten Hälfte des letzten Jahrhunderts das Verhältnis von Mensch und Natur durch
die Wahrnehmung einer Umweltkrise zunehmende Bedeutung (Hardin, 1968, White,
1968). In diesem Zusammenhang kann Kants „Was soll ich tun?“ konkretisiert werden
als „Wie habe ich mich gegenüber der natürlichen Mitwelt richtig zu verhalten?“. Die
Ökologie kann keine Antwort auf diese Frage liefern, da sie normative Aussagen
fordert, die jenseits des beschreibenden und erklärenden Charakters der
Naturwissenschaften stehen (Hume, 1978, Valsangiacomo, 1998). Unsere Vorstellung
vom richtigen Umgang mit der natürlichen Mitwelt ist Teil des gesellschaftlichen
Diskurses und manifestiert sich, zum Beispiel, in der Umweltpolitik. Hier bildet sie den
moralischen Hintergrund, vor dem die angewandte Naturwissenschaft agiert.
Die vorliegende Dissertation beinhaltet angewandte Wissenschaft zur Umsetzung der
Europäischen Wasserrahmenrichtlinie (Europäische Kommission, 2000). Dieses
Umweltgesetz schafft einen Ordnungsrahmen für Maßnahmen im Bereich der
Wasserpolitik für die 27 Mitgliedstaaten der Europäischen Gemeinschaft. Die Richtlinie
fordert von den Mitgliedstaaten eine ökologischen Zustandsbewertung ihrer Flüsse,
Seen, Küstengewässer und Ästuare (Flussmündungen). Anhand von
Bewertungsverfahren bestimmen die Länder den Zustand ausgewählter aquatischer
Tier- und Pflanzengruppen, den so genannten biologischen Qualitätskomponenten.
Diese Verfahren unterscheiden zwischen verschiedenen Typen von
Oberflächengewässern. Bezugspunkt der Bewertung ist der vom Menschen
unbeeinträchtigte Gewässerzustand, dass heißt der Referenzzustand, welcher je nach
Gewässertyp unterschiedlich ausgeprägt ist. Die Ergebnisse der nationalen
Bewertungsverfahren werden als relative Übereinstimmung mit dem Referenzzustand
dargestellt im so genannten „Ecological Quality Ratio“ (EQR). Je nach Grad der
Übereinstimmung erfolgt die Beurteilung des ökologischen Zustands in den Klassen
sehr gut, gut, mäßig, unbefriedigend oder schlecht (Birk & Böhmer, 2007).
Zusammenfassung
Die Wasserrahmenrichtlinie fordert den guten ökologischen Zustand für alle
Wasserkörper und definiert diesen Zustand über normative Begriffsbestimmungen
(Europäische Kommission, 2000, S. 38):
„Die Werte für die biologischen Qualitätskomponenten des Oberflächen-
gewässertyps zeigen geringe anthropogene Abweichungen an, weichen aber nur
in geringem Maße von den Werten ab, die normalerweise bei Abwesenheit
störender Einflüsse mit dem betreffenden Oberflächengewässertyp einhergehen.“
Die Definition des guten ökologischen Zustands stellt ein Schlüsselelement in der
Europäischen Wasserpolitik dar. Die Gemeinschaft verpflichtet ihre Mitgliedstaaten
zum richtigen Umgang mit der aquatischen Umwelt und schreibt das Ergreifen von
geeigneten Maßnahmen vor, wenn diese Zielsetzung verfehlt wird. Das Konzept des
guten ökologischen Zustands ist daher von entscheidender Bedeutung bei der
Umsetzung der Wasserrahmenrichtlinie. Dennoch überlässt es die Richtlinie den
Mitgliedstaaten, auf welche Weise diese recht unkonkrete Definition in die Praxis
umgesetzt wird. Die Länder selbst stehen in der Verantwortung, die
Bewertungsverfahren zu entwickeln und damit den Zustand ihrer Wasserkörper
einzustufen. Um die nationalen Interpretationen des guten ökologischen Zustands zu
vergleichen und zu harmonisieren, schreibt die Richtlinie die so genannte
Interkalibrierung vor (Heiskanen et al., 2004).
Die Interkalibrierung zielt darauf ab, für alle Mitgliedstaaten einen vergleichbaren
Anspruch im Gewässerschutz zu schaffen. Aufgabe der Interkalibrierung ist, die
europaweit einheitliche Bewertung des guten ökologischen Zustands durch die
nationalen Bewertungsverfahren zu gewährleisten. Vereinfacht ausgedrückt: Die
Interkalibrierung soll sicherstellen, dass zum Beispiel ein Wasserkörper in Belgien, der
von dem belgischen Verfahren als „gut“ bewertet wird, auch vom deutschen und
niederländischen Verfahren als „gut“ eingestuft würde, wenn sich derselbe
Wasserkörper auf deutschem oder holländischem Gebiet befände (Birk & Böhmer,
2007). Allerdings zeigen die Gewässer eines vergleichbaren Typs Unterschiede in
Fauna und Flora zwischen den Ländern, auch unter vom Menschen unbeeinflussten
Bedingungen. Darüber hinaus sind die nationalen Verfahren durch verschiedene
Bewertungskonzepte und -traditionen gekennzeichnet (Birk, 2003, Birk & Schmedtje,
2005). Werden nur Flüsse und Seen berücksichtigt, in denen jeweils vier
98
Zusammenfassung
Qualitätskomponenten bewertet werden (Phytoplankton, Phytobenthos und
Makrophyten, Makrozoobenthos, Fische), sind allein schon über 200 nationale
Verfahren zwischen den 27 Mitgliedstaaten zu interkalibrieren (Birk et al., 2009). Dies
gibt einen Eindruck von der schwierigen und komplexen Aufgabe der Interkalibrierung.
Die vorliegende Arbeit schafft die methodische Basis für die technische Umsetzung der
Interkalibrierung. Die grundlegende Fragestellung lautet: Wie können die nationalen
Definitionen des guten ökologischen Zustands am besten verglichen werden? Dabei
kommen die Ansätze des direkten Verfahrensvergleichs sowie des indirekten
Vergleichs anhand von Allgemeinen Metriks6 zur Anwendung. In vier Fallstudien
untersuche ich (1) die numerischen Zusammenhänge der nationalen
Bewertungsverfahren, (2) die Rolle unterschiedlicher Definitionen von
Referenzzuständen innerhalb der Interkalibrierung sowie (3) die Möglichkeiten einer
einheitlichen Festlegung des guten ökologischen Zustands. Die vier Fallstudien
behandeln insgesamt 26 nationale Verfahren zur Bewertung des ökologischen
Zustands von Fließgewässern anhand von Makrozoobenthos (15 Verfahren),
Makrophyten (9 Verfahren) und benthischen Diatomeen (2 Verfahren). Für die
verschiedenen Analysen werden mehr als 1.900 biologische Probenahmen genutzt,
welche im Rahmen von Europäischen Forschungsprojekten oder Programmen der
nationalen Gewässerüberwachung erhoben wurden. Die Arbeit deckt drei
Interkalibrierungstypen7 Mitteleuropas ab, sowie vier Interkalibrierungstypen in
Osteuropa.
1 Direkter Vergleich von nationalen Verfahren zur Bewertung des Makrozoobenthos in Fließgewässern
In der ersten Fallstudie untersuchte ich die numerischen Zusammenhänge von zehn
Verfahren zur Bewertung des Makrozoobenthos in Fließgewässern. Datengrundlage
bildeten Probenahmen, die durch eine einheitliche Methode in Rahmen der
6 Unabhängig von den naturräumlichen Gegebenheiten und den spezifischen Formen der
Gewässerbelastung eines Landes erfassen Allgemeine Metriks die generelle Belastung eines Gewässers durch den Menschen, wenn auch in etwas unschärferer Weise als die national angepassten Verfahren.
7 Die Interkalibrierungstypen umfassen Gewässer mit vergleichbaren Merkmalen, die in verschiedenen Ländern vorkommen. Ihre Ausweisung stützt sich auf die Beschreibung ausgewählter Parameter, wie Ökoregion, Größe, Höhenlage, Geologie oder Sohlsubstrat.
99
Zusammenfassung
Forschungsprojekte AQEM8 und STAR9 erhoben wurden (Hering et al., 2004, Furse et
al., 2006). Die Daten wurden getrennt für zwei Interkalibrierungstypen Mitteleuropas
analysiert. 294 Probenahmen an 125 Stellen in Deutschland, Österreich, Tschechien
sowie der Slowakei ließen sich dem Gewässertypen der silikatischen
Mittelgebirgsbäche zuordnen. Die kleinen Flüsse des Tieflands waren durch 217
Proben an 71 Gewässerstellen in Dänemark, Deutschland, Großbritannien und
Schweden vertreten. Neben den biologischen Daten zu taxonomischer
Zusammensetzung und Abundanz des Makrozoobenthos waren diverse physiko-
chemische Parameter, die hydromorphologische Qualität sowie Daten zur
Landnutzung in Gewässerumfeld und Einzugsgebiet verfügbar. Ferner wurde der
ökologische Zustand jeder Probestelle vor Ort durch den jeweiligen Probenehmer
voreingestuft. Die untersuchten Bewertungsverfahren umfassten Saprobienindizes und
weitere biologische Metriks, die in der nationalen Gewässerüberwachung von
Dänemark, Deutschland, Großbritannien, Polen, Schweden, der Slowakei, Tschechien
oder Österreich angewendet werden. Diese Länder definierten Grenzwerte für die
Einstufung des guten ökologischen Zustands, welche in dieser Studie die Grundlage
für den Vergleich der Zustandsbewertungen darstellten.
Auf Basis der Makrozoobenthos-Daten erfolgte für jede Probenahme die Berechnung
der biologischen Indizes. Die Auswahl des 75. Perzentilwerts innerhalb der als „sehr
gut“ voreingestuften Probestellen ermöglichte eine einheitliche Festlegung von
Gewässertyp-spezifischen Referenzwerten. Die Werte eines jeden nationalen Index’
konnten somit als EQR dargestellt werden. Die Korrelation der nationalen EQR sowie
die Art ihres Zusammenhangs (linear, nichtlinear) wurden durch Regressionsanalyse
bestimmt. Um die Definitionen der nationalen Klassengrenzen des guten ökologischen
Zustands zu vergleichen, wurden zwei Vergleichsskalen definiert: (1) Der nationale
Index, der die höchste mittlere Korrelation zu allen Bewertungsverfahren aufwies, und
(2) der so genannte „Integrative Multimetric Index for Intercalibration“ (IMI-IC), der sich
aus dem Mittelwert aller nationalen Bewertungsverfahren pro Probestelle
zusammensetzte. Die nationalen Grenzwerte wurden mit Hilfe der
8 “The Development and Testing of an Integrated Assessment System for the Ecological Quality of
Streams and Rivers throughout Europe using Benthic Macroinvertebrates.” Forschungsprojekt im fünften Rahmenprogramm der Europäischen Kommission.
9 “Standardisation of River Classifications: Framework method for calibrating different biological survey results against ecological quality classifications to be developed for the Water Framework Directive.” Forschungsprojekt im fünften Rahmenprogramm der Europäischen Kommission.
100
Zusammenfassung
Regressionsfunktionen in Werte der Vergleichsskalen übertragen, und für jeden Wert
wurde das 95-Prozent-Konfidenzintervall berücksichtigt. Eine mit den Umweltvariablen
durchgeführte Hauptkomponentenanalyse bestimmte, welche Form von anthropogener
Belastung im Datensatz eines Interkalibrierungstypen am stärksten ausgeprägt ist.
Mittels linearer Regression wurde den nationalen Klassengrenzen des guten Zustands
ein korrespondierender Belastungsgrad inklusive des Konfidenzintervalls zugewiesen.
Die Analysen zeigten, dass die einheitlich festgelegten Referenzwerte strenger als die
national definierten Werte ausfielen. Der mittlere Determinationskoeffizient (R2) aller
Regressionen der nationalen Verfahren war größer als 0,5. Der deutsche
Saprobienindex korrelierte am höchsten für den Datensatz der Mittelgebirgsbäche. Für
die Proben der kleinen Tieflandflüsse ergab der dänische Flussfaunaindex die
höchsten mittleren R2-Werte. Die Koeffizienten des IMI-IC lagen im Mittel um 0,8.
Vornehmlich wiesen nichtlineare Zusammenhänge gegenüber linearen Beziehungen
höhere Determinationskoeffizienten auf. Allerdings waren diese Unterschiede nicht
signifikant, daher setzte ich für die weiteren Analysen einen linearen Bezug voraus. Die
Hauptkomponentenanalyse zeigte, dass die Daten der Mittelgebirgsbäche durch einen
Gradienten der Nährstoffbelastung und organischen Verschmutzung geprägt waren.
Die Probenahmen an den kleinen Tieflandflüssen bildeten einen
hydromorphologischen Gradienten ab. Generell waren die Bewertungsergebnisse der
Mittelgebirgsbäche höher mit dem dort vorherrschenden Belastungsgradienten
korreliert. Der Vergleich der nationalen Klassengrenzen über die beiden
Vergleichsskalen zeigte Abweichungen von bis zu 25 Prozent. Je nach Skala waren
unterschiedliche Abweichungen zu verzeichnen. Anhand der Regression mit den
Belastungsgradienten konnten Gruppen mit einheitlicher Grenzdefinition bestimmt
werden.
2 Interkalibrierung von Bewertungsverfahren für Makrophyten in Flüssen des Tieflands: direkter Vergleich und Analyse von Allgemeinen Metriks
Die zweite Fallstudie untersuchte zwei verschiedene Optionen des Vergleichs
nationaler Bewertungsverfahren anhand von Makrophyten in Fließgewässern.
Datengrundlage bildeten 108 nach harmonisiertem Protokoll erhobene
Vegetationsaufnahmen an kleinen Flüssen des Tieflands (Dänemark, Deutschland,
Großbritannien, Lettland, Polen, Schweden; Furse et al., 2006). Diese Stellen wurden
jeweils mit vier nationalen Verfahren bewertet. Hierzu mussten die vorliegenden
101
Zusammenfassung
Angaben zum Deckungsgrad der Makrophyten-Arten in die nationalen
Häufigkeitsskalen übersetzt werden. Einheitliche Referenzwerte leitete ich über das 95.
Perzentil der Indexwerte aller Vegetationsaufnahmen ab. Auf Grundlage der
Vegetationsaufnahmen wurden 70 biologische Metriks berechnet und mit den
nationalen Bewertungsindizes in Relation gesetzt. Ziel war die Bestimmung sowohl von
nationalen Indizes als auch Allgemeinen Metriks, die mit allen nationalen Verfahren
korrelieren. Aus einer Hauptkomponentenanalyse gewonnene Umweltgradienten
dienten zur Dokumentation einer Dosis-Wirkungs-Beziehung zwischen menschlicher
Belastung und Reaktion der Makrophytenindizes. Zwei Vergleichsskalen erlaubten die
Überprüfung der nationalen Definitionen des guten ökologischen Zustands. Die
Übertragung dieser Werte erfolgte durch die aus der Regressionsanalyse
resultierenden Kurvengleichungen.
Die nationalen Einstufungen des ökologischen Zustands differierten erheblich zwischen
den Bewertungsverfahren. Ebenso fielen die einheitlich definierten Referenzwerte in
unterschiedliche nationale Zustandsklassen. Das holländische Verfahren bewertete am
strengsten; alle Probestellen wurden als mäßig oder schlechter klassifiziert. Die
Bewertungsergebnisse der Indizes aus Frankreich und Großbritannien wiesen einen
Determinationskoeffizienten von größer 0,75 auf. Das deutsche und niederländische
Verfahren war geringer mit diesen Indizes korreliert. Bei der Regression vor allem des
deutschen Verfahrens wurden nichtlineare Zusammenhänge deutlich. Von den 70
Makrophytenmetriks erwies sich nur ein auf Nährstoffzeigern basierender Index
(Ellenberg et al., 1992) als Allgemeiner Metrik brauchbar. Dieser Metrik zeigte
deutliche Beziehungen zum britischen, deutschen und französischen Verfahren,
korrelierte aber schwach negativ mit dem holländischen Index. Aus diesem Grund
wurde das niederländische Verfahren vom anschließenden Vergleich der
Zustandsklassen ausgeschlossen. Dieser Vergleich offenbarte starke Unterschiede
zwischen den nationalen Klassengrenzen. Außerdem erschwerten die nichtlinearen
Beziehungen eine Übertragung der nationalen Grenzen in Werte der Vergleichsskalen.
Ferner waren alle außer dem niederländischen Verfahren mit dem Nährstoffgradienten
korreliert. Der holländische Index reagierte sensitiv gegenüber genereller Degradation.
102
Zusammenfassung
3 Schaffung einer gemeinsamen Basis für die Europäische Bewertung von Makrophyten in Fließgewässern
Die Ergebnisse des zweiten Kapitels verdeutlichten die Notwendigkeit weiterer
Forschung bezüglich der Interkalibrierung von Makrophyten-Verfahren. Vor diesem
Hintergrund wurden in einer dritten Fallstudie 609 Vegetationsaufnahmen aus den
nationalen Überwachungsprogrammen von zwölf Europäischen Mitgliedstaaten
zusammengetragen. Ziel der Studie war die Schaffung einer gemeinsamen Basis für
den Vergleich der nationalen Bewertungen anhand von Makrophyten. Untersucht
wurden die Verfahren von Belgien, Deutschland, Frankreich, Großbritannien,
Österreich und Polen. Die biologischen Daten umfassten taxonomische
Zusammensetzung und Häufigkeit von Fließgewässer-Makrophyten für die
Interkalibrierungstypen der silikatischen Mittelgebirgsbäche, der silikatischen
Sandbäche des Tieflands sowie der kleinen Flüsse des Tieflands. Bei den Tiefland-
Typen beschränkten sich die Analysen auf Gewässerstellen mit mittlerem bis hohem
Säurebindungsvermögen (Alkalinität).
Im Vorfeld der Analysen wurden Taxonomie und Häufigkeitsskalen harmonisiert und
den Arten ein Grad der Wassergebundenheit („level of aquaticity“) zugewiesen. Alle
Vegetationsaufnahmen wurden durch die nationalen Verfahren bewertet, dann wurden
innerhalb eines Interkalibrierungstypen alle nationalen Bewertungsergebnisse pro
Vegetationsaufnahme gemittelt. In einem nächsten Schritt wurde dieser mittlere Index
mit den Häufigkeiten der in den Vegetationsaufnahmen vorkommenden Makrophyten-
Arten korreliert. Die lineare Beziehung von Arten-Häufigkeit und mittlerem Index wurde
über den Korrelationskoeffizienten nach Spearman gemessen. Die Analyse ergab
einen Korrelationskoeffizienten für jede Art und umfasste ein Wertespektrum, welches
Arten entweder als positiv, negativ oder nicht signifikant korreliert zum mittleren Index
auswies. Die Korrelationskoeffizienten wurden zur Festlegung von Art-spezifischen
Indikatorwerten genutzt, welche die Beschreibung von Gewässertyp-spezifischen
Makrophytengemeinschaften unter ungestörten bzw. degradierten Bedingungen
ermöglichte. Die Indikatorwerte wurden außerdem zur Berechnung des Allgemeinen
Metriks „macrophyte Intercalibration Common Metric“ (mICM) verwendet.
Auf Grundlage der Vegetationsaufnahmen wurde der mICM gegen die einzelnen
nationalen Bewertungsergebnisse aufgetragen. Lineare und nichtlineare (quadratische)
Regressionsmodelle wurden angewendet, anschließend die resultierenden
103
Zusammenfassung
Bestimmtheitsmaße (R2) überprüft. Im Falle geringer R2-Werte wurden die mICM-
Indikatorwerte mit den jeweiligen nationalen Werten der entsprechenden Arten
verglichen. Deutliche Unterschiede beider Indikatorwerte wurden durch
Änderungsvorschläge für die nationalen Werte angeglichen. Allerdings fanden nur
solche Änderungen statt, die einen wesentlichen Anstieg des Bestimmtheitsmaßes in
den wiederholten Regressionsanalysen zur Folge hatten. Einheitliche Referenzwerte
wurden über die Definition von Probestellen im allgemein sehr guten Zustand
hergeleitet.
Dieser Ansatz erwies sich als tragfähige Methodik zur Schaffung einer gemeinsamen
Basis für die Interkalibrierung. Für die drei Gewässertypen konnte eine umfangreiche
Beschreibung der Makrophytengemeinschaften und ihrer Umweltbedingungen im
naturnahen und belasteten Zustand erstellt werden. Diese Darstellungen fungierten als
Leitbild im Prozess der Harmonisierung der Bewertungsverfahren. Mit dem mICM
wurde ein geeigneter Allgemeiner Metrik entwickelt. Auf Grundlage des Leitbildes
wurden die Indikatorwerte ausgewählter Arten im belgischen und deutschen Verfahren
angepasst. In den Regressionsanalysen wies der mICM einen mittleren R2-Wert von
über 0,6 zu allen nationalen Verfahren auf. Die Werte dieses Metriks zeigten eine
geringe Spannweite innerhalb der Probestellen im allgemein sehr guten Zustand.
Diese Eigenschaft würde die Definition äquidistanter Klassengrenzen zum Zwecke des
Vergleichs mit den nationalen Grenzsetzungen erlauben.
4 Eine neue Methode zum Vergleich von Klassengrenzen biologischer Bewertungsverfahren: ein Fallbeispiel aus dem Donau-Stromgebiet
In der vierten Fallstudie dieser Arbeit wurden die Einstufungen des ökologischen
Zustands für verschiedene Makrozoobenthos- und Diatomeen-Verfahren in Osteuropa
verglichen und harmonisiert. Grundlage für die Analysen bildeten Daten aus den
nationalen Überwachungsprogrammen von Österreich, Bulgarien, Rumänien, der
Slowakei und Ungarn. Biologische Aufnahmen von Gewässerstellen in naturnahem
Zustand waren nicht verfügbar. Deshalb testete ich einen alternativen Ansatz zur
Festlegung von Referenzen für die Interkalibrierung. Für vier Interkalibrierungstypen
wurden Probestellen im wenigstens guten Umweltzustand ausgewiesen. Hierzu nutzte
ich Grenzwerte für die Parameter Gesamt- und Orthophosphat, Biologischer
Sauerstoffbedarf, Leitfähigkeit, hydromorphologischer Zustand und Landnutzungsindex
(Böhmer et al., 2004). Der biologische Metrik „Average Score Per Taxon“ (Armitage et
104
Zusammenfassung
al., 1983) wurde als zusätzlicher Parameter für die Gewässerstellen mit
Makrozoobenthos-Aufnahmen gewählt. Als Skalen für den Vergleich bzw. die
Harmonisierung der nationalen Klassengrenzen dienten Allgemeine Metriks. Für das
Makrozoobenthos wurde in dieser Studie ein multimetrischer Interkalibrierungs-Index
entwickelt. Die Diatomeen-Verfahren verglich ich mit dem Allgemeinen Metrik, der von
Kelly et al. (2008) im mitteleuropäischen Interkalibrierungsprozess angewendet wurde.
Anhand der biologischen Daten wurden sowohl die nationalen Bewertungsverfahren
als auch die Allgemeinen Metriks berechnet. Die Verteilungen der Ergebnisse der
Allgemeinen Metriks innerhalb der Gewässerstellen im wenigstens guten
Umweltzustand ermöglichten die Definition transnationaler Bezugspunkte („biological
benchmarks“) für die Interkalibrierung. Diese Bezugspunkte dienten zur Normalisierung
der Werte der Allgemeinen Metriks. Somit konnten die nationalen Klassengrenzen der
Diatomeen-Verfahren Österreichs und der Slowakei in Regressionsanalysen verglichen
werden. Dabei zeigten sich zwischen den Verfahren Unterschiede sowohl in der
Festsetzung der nationalen Referenzwerte als auch der Werte für die Klassengrenze
sehr gut - gut. Beim Makrozoobenthos ermöglichte die „Benchmarking“-Methode die
einheitliche Festlegung der Klassengrenzen des guten ökologischen Zustands, ohne
Rückgriff auf die nationalen Grenzdefinitionen. Diese Vorgehensweise erlaubte die
Interkalibrierung von Ländern, deren Verfahren noch in der Entwicklung standen. Die
Ergebnisse dieser Studie bildeten Bestandteil der Entscheidung der Europäischen
Kommission zur Festlegung der Grenzwerte des guten ökologischen Zustands
(European Commission, 2008).
Schlussbetrachtungen
Meine Untersuchungen zur Fragestellung, wie die nationalen Definitionen des guten
ökologischen Zustands am besten verglichen werden können, zeigten unterschiedlich
starke numerische Zusammenhänge zwischen den Bewertungsergebnissen der
nationalen Verfahren. Makrozoobenthos- und Diatomeen-Verfahren waren
untereinander und gegenüber Allgemeinen Metriks hoch korreliert, Makrophyten-
Verfahren wiesen schwächere Zusammenhänge auf. Differierende
Bewertungskonzepte und -traditionen zwischen den biologischen
Qualitätskomponenten sind hier von wesentlicher Bedeutung. Des weiteren
untersuchte ich verschiedene Ansätze für eine einheitliche Definition von
105
Zusammenfassung
Referenzzuständen. Neben der Anwendung von nicht-biologischen Kriterien, welche
Gewässerstellen als naturnah oder gering gestört auswiesen, wurden auch rein
biologisch festgelegte Referenzzustände genutzt (beste, verfügbare Gewässerstellen;
Stellen im allgemein sehr guten Zustand). Die Art ihrer Festlegung ist von zentralem
Stellenwert für die Interkalibrierung. Der Vergleich und die Harmonisierung des guten
ökologischen Zustands bildeten einen dritten Schwerpunkt innerhalb dieser Arbeit. Alle
Untersuchungen offenbarten Unterschiede in den nationalen Festsetzungen der
Zustandsklassen. Eine Harmonisierung ließ sich sowohl über den Abgleich mit nicht-
biologischen Daten zur Gewässerbelastung als auch über die Definition transnationaler
Bezugspunkte erreichen.
Durch den Interkalibrierungsprozess wird ein grenzüberschreitendes Konzept für den
guten ökologischen Zustand geschaffen, das von hoher sozioökonomischer Bedeutung
ist: Die Europäischen Mitgliedstaaten sind verpflichtet, diesen Zustand zu erhalten oder
durch geeignete Maßnahmen wieder herzustellen. Vor diesem Hintergrund ist eine
kritische Prüfung der Methoden der Interkalibrierung hinsichtlich ihrer Gültigkeit und
Beschränkungen unabdingbar. Die Wasserrahmenrichtlinie basiert auf einer
bestimmten Naturwahrnehmung, die vom Konzept einer statischen, nicht-dynamischen
Umwelt geprägt ist, und in der ein vom Menschen unbeeinflusster Zustand das Leitbild
für menschliches Handeln darstellt. Diese Voraussetzungen schaffen den
grundsätzlichen Rahmen für ökologische Zustandsbewertung und Interkalibrierung.
Der Einfluss von Unsicherheiten auf die Ergebnisse von Bewertung und
Interkalibrierung blieb im Prozess weitgehend unberücksichtigt. Ferner kann die
Verpflichtung zur Interkalibrierung innovative Ansätze der Gewässerbewertung
verhindern, wenn sich diese als unvergleichbar mit den herkömmlichen Verfahren
erweisen. Und letztlich bleibt jede naturwissenschaftliche Festlegung des guten
Zustands willkürlich: Das Studium der Natur kann uns keine normativen Aussagen zum
richtigen Umgang mit der natürlichen Mitwelt liefern.
Der Interkalibrierungsprozess initiierte einen europaweiten Diskurs über biologische
Gewässerbewertung und die Definition des guten ökologischen Zustands. Innerhalb
dieses Diskurses bildet die vorliegende Arbeit einen wichtigen Beitrag zur
wissenschaftlichen Umsetzung der Vorgaben der EG-Wasserrahmenrichtlinie.
106
References
107
References
Alba-Tercedor, J. & A.M. Pujante, 2000. Running-water biomonitoring in Spain:
opportunities for a predictive approach. In Wright, J. F., D. W. Sutcliffe & M. T. Furse
(Editors), Assessing the biological quality of fresh waters - RIVPACS and other
techniques. FBA, Ambleside: 207-216.
Allan, D.J., 2004. Landscapes and Riverscapes: the influence of land use on stream
ecosystems. Annual Review of Ecology, Evolution and Systematics 35: 257-284.
Armitage, P.D., D. Moss, J.F. Wright & M.T. Furse, 1983. The performance of a new
biological water quality score system based on macroinvertebrates over a wide range
of unpolluted running-water sites. Water Research 17: 333-347.
Baattrup-Pedersen, A. & T. Riis, 1999. Macrophyte diversity and composition in relation
to substratum characteristics in regulated and unregulated Danish streams. Freshwater
Biology 42: 375-385.
Baattrup-Pedersen, A., G. Springe, T. Riis, S.E. Larsen, K. Sand-Jensen & L.M.
Kjellerup-Larsen, 2008. The search for reference conditions for stream vegetation in
northern Europe. Freshwater Biology 53: 1890-1901.
Biggs, J., 2006. European Environmental NGO Technical Review of the Water
Framework Directive Intercalibration Process. European Environmental Bureau, Royal
Society for the Protection of Birds and Pond Conservation, Brussels.
Biggs, J., A. Corfield, D. Walker, M. Whitfield & P. Williams, 1996. A preliminary
comparison of European methods of biological river water quality assessment. NRA
Thames Region Operational Investigation. Environment Agency Technical Report No.
0I/T/001. National Rivers Authority Thames Region, Reading.
Birk, S., 2003. Review of European assessment methods for rivers and streams using
benthic invertebrates, aquatic flora, fish and hydromorphology. Diploma thesis.
University of Duisburg-Essen, Essen.
Birk, S. & D. Hering, 2002. Waterview Web-Database: a comprehensive review of
European assessment methods for rivers. FBA News 20: 4.
Birk, S. & P. Rolauffs, 2004. A preliminary study comparing the results between the
Austrian, Czech and German saprobic systems for the intercalibration of cross-border
river basin districts. In Deutsche Gesellschaft für Limnologie (DGL) - Tagungsbericht
(Köln). DGL, Werder: 74-79.
Birk, S. & U. Schmedtje, 2005. Towards harmonization of water quality classification in
the Danube River Basin: overview of biological assessment methods for running
waters. In: J. Bloesch (Editor), River basin management: concepts and transboundary
References
implementation (with special reference to the Danube River). Archiv für Hydrobiologie
Supplement Large rivers, 16: 171-196.
Birk, S. & J. Böhmer, 2007. Die Interkalibrierung nach EG-Wasserrahmenrichtlinie -
Grundlagen und Verfahren. Wasserwirtschaft 9: 10-14.
Birk, S., N. Willby, C. Chauvin, H.C. Coops, L. Denys, D. Galoux, A. Kolada, K. Pall, I.
Pardo, R. Pot & D. Stelzer, 2007a. Report on the Central Baltic River GIG Macrophyte
Intercalibration Exercise, June 2007.
Birk, S., J. Böhmer, C. Meier, P. Rolauffs, J. Schaumburg & D. Hering, 2007b. EG-
Wasserrahmenrichtlinie - Harmonisierung der Berichterstattung zur ökologischen
Einstufung nach EG-Wasserrahmenrichtlinie (Interkalibrierung biologischer
Untersuchungsverfahren in Deutschland). University of Duisburg-Essen, Essen.
Birk, S., E. Bellack, J. Böhmer, K. Bunzel, F. Fischer, A. Kolbinger, U. Mischke, J.
Schaumburg & C. Schütz, 2009. Die Interkalibrierung nach EG-Wasserrahmenrichtlinie
- Ergebnisse der ersten Interkalibrierungsphase 2005-2007. Wasserwirtschaft 5: 20-25.
BMLFUW, 2006a. Leitfaden für die Erhebung der Biologischen Qualitätselemente.
Arbeitsanweisung Fließgewässer. A4-01a Qualitätselement Makrophyten:
Felderhebung, Probenahme, Probenaufbereitung und Ergebnismitteilung. Dezember
2006. Bundesministerium für Land- und Forstwirtschaft, Umwelt und Wasserwirtschaft,
Wien.
BMLFUW, 2006b. Leitfaden für die Erhebung der Biologischen Qualitätselemente.
Arbeitsanweisung Fließgewässer. A2-01a Qualitätselement Makrozoobenthos:
Felderhebung, Probenahme, Probenaufbereitung und Ergebnismitteilung. Oktober
2006. Bundesministerium für Land- und Forstwirtschaft, Umwelt und Wasserwirtschaft,
Wien.
BMWP (Biological Monitoring Working Party), 1978. Final Report of the Biological
Monitoring Working Party: Assessment and presentation of the biological quality of
rivers in Great Britain. Department of the Environmental Water Data Unit, London.
Böhmer, J., C. Rawer-Jost, A. Zenker, C. Meier, C.K. Feld, R. Biss & D. Hering, 2004.
Assessing streams in Germany with benthic invertebrates: Development of a
multimetric invertebrate based assessment system. Limnologica 34: 416-432.
Borja, A., A.B. Josefson, A. Miles, I. Muxika, F. Olsgard, G. Phillips, J.G. Rodríguez &
B. Rygg, 2007. An approach to the intercalibration of benthic ecological status
assessment in the North Atlantic ecoregion, according to the European Water
Framework Directive. Marine Pollution Bulletin 55: 42-52.
Bossard, M., J. Feranec & J. Otahel, 2000. CORINE land cover technical guide -
Addendum 2000. European Environment Agency, Copenhagen.
108
References
Brabec, K., S. Zahradkova, D. Nemejcova, P. Paril, J. Kokes & J. Jarkovsky, 2004.
Assessment of organic pollution effect considering differences between lotic and lentic
stream habitats. Hydrobiologia 516: 331-346.
Braun-Blanquet, J., 1928: Pflanzensoziologie. Grundzüge der Vegetationskunde.
Springer, Berlin.
Buffagni, A., S. Erba, M. Cazzola & J. L. Kemp, 2004. The AQEM multimetric system
for the southern Italian Apennines: assessing the impact of water quality and habitat
degradation on pool macroinvertebrates in Mediterranean rivers. Hydrobiologia 516:
313-329.
Buffagni, A., S. Erba, S. Birk, M. Cazzola, C. Feld, T. Ofenböck, J. Murray-Bligh, M. T.
Furse, R. T. Clark, D. Hering, H. Soszka & W. v. d. Bund, 2005. Towards European
Inter-calibration for the Water Framework Directive: Procedures and examples for
different river types from the E.C. project STAR. 11th STAR deliverable. STAR
Contract No: EVK1-CT 2001-00089. Quaderni Istituto di Ricerca sulle Acque 123: 1-
468.
Buffagni, A., S. Erba, M. Cazzola, J. Murray-Bligh, H. Soszka & P. Genoni, 2006. The
STAR common metrics approach to the WFD intercalibration process: full application
for small, lowland rivers in three European countries. In: M.T. Furse, D. Hering, K.
Brabec, A. Buffagni, L. Sandin and P.F.M. Verdonschot (Editors), The ecological status
of European rivers. Evaluation and intercalibration of assessment methods.
Hydrobiologia, 566: 379-399.
Buffagni, A., S. Erba & M.T. Furse, 2007. A simple procedure to harmonize class
boundaries of assessment systems at the pan-European scale. Environmental Science
and Policy 10: 709-724.
Carstensen, J., 2007. Statistical principles for ecological status classification of Water
Framework Directive monitoring data. Marine Pollution Bulletin 55: 3-15.
CB GIG Lakes, 2008. Central Baltic GIG Lakes. WFD intercalibration technical report.
Part 2 - Lakes. Section 2 – Chlorophyll-a concentration. Joint Research Centre, Ispra.
CB GIG Rivers, 2008. Central Baltic GIG Rivers. WFD intercalibration technical report.
Part 1 - Rivers. Section 2 - Benthic macroinvertebrates. Joint Research Centre, Ispra.
CEMAGREF (Centre National du Machinisme Agricole du Génie Rural, des Eaux et
des Forets), 1982. Etude des méthodes biologiques d'appréciation quantitative de la
qualité des eaux. Rapport Q.E. Lyon. Division Qualité des Eaux - Pêche et Pisciculture,
Lyon.
109
References
Clarke, R.T., M.T. Furse, J.F. Wright & D. Moss, 1996. Derivation of a biological quality
index for river sites : comparison of the observed with the expected fauna. Journal of
Applied Statistics 23: 311-332.
Clarke, R., A. Lorenz, L. Sandin, A. Schmidt-Kloiber, J. Strackbein, N. T. Kneebone &
P. Haase, 2006. Effects of sampling and sub-sampling variation using the STAR-
AQEM sampling protocol on the precision of macroinvertebrate metrics. In: M.T. Furse,
D. Hering, K. Brabec, A. Buffagni, L. Sandin and P.F.M. Verdonschot (Editors), The
ecological status of European rivers. Evaluation and intercalibration of assessment
methods. Hydrobiologia, 566: 441-459.
Council of the European Communities, 1991. Urban Waste Water Treatment Directive
91/271/EEC. Official Journal of the European Communities, L135/40-52, 30 May 1991,
Brussels.
CSN 757716, 1998. Water quality, biological analysis, determination of saprobic index.
Czech Technical State Standard, Czech Standards Institute, Prague.
Dell'Uomo, A., 1996. Assessment of water quality of an Apennine river as a pilot study
for diatom-based monitoring of Italian watercourses. In: B.A. Whitton & E. Rott
(Editors), Use of algae for monitoring rivers II: proceedings of an international
symposium held at the Volksbildungsheim Grillhof, Vill near Innsbruck. Rott, Innsbruck:
65-72.
Descy, J.-P. & M. Coste, 1991. A test of methods for assessing water quality based on
diatoms. Verhandlungen der internationalen Vereinigung für theoretische und
angewandte Limnologie 24: 2112-2116.
Deutsch, K. & N. Kreuzinger, 2005. Leitfaden zur typspezifischen Bewertung der
allgemeinen chemisch/physikalischen Parametern in Fließgewässern.
Bundesministerium für Land- und Forstwirtschaft, Umwelt und Wasserwirtschaft, Wien.
ECOSTAT (CIS WG 2.A Ecological Status), 2004a. Guidance on the intercalibration
process. Agreed version of WG 2.A Ecological Status meeting held 7-8 October 2004
in Ispra. Version 4.1 - 14 October 2004. ECOSTAT, Ispra.
ECOSTAT (CIS WG 2.A Ecological Status), 2004b. Overview of common
intercalibration types. Final version for finalisation of the intercalibration network spring
2004. Version 5.1 - 23 April 2004. ECOSTAT, Ispra.
Elbersen, J.W.H., P.F.M. Verdonschot, B. Roels & J.G. Hartholt, 2003. Definitiestudie
KaderRichtlijn Water (KRW). I. Typologie Nederlandse Oppervlaktewateren. Alterra-
rapport 669. ALTERRA, Wageningen.
Ellenberg, H., H.E. Weber, R. Düll, V. Wirth, W. Werner & D. Paulißen, 1992. Indicator
values of plants in Central Europe. Erich Goltze, Göttingen.
110
References
EN 13946:2003. Water quality. Guidance standard for the routine sampling and pre-
treatment of benthic diatoms from rivers. European Committee for Standardization,
Brussels.
EN 14184:2003, Water quality - Guidance standard for the surveying of aquatic
macrophytes in running waters. European Committee for Standardization, Brussels.
EN 27828:1994. Water quality - Methods of biological sampling - Guidance on handnet
sampling of aquatic benthic macro-invertebrates (ISO 7828:1985). European
Committee for Standardization, Brussels.
European Commission, 2000. Directive 2000/60/EC. Establishing a framework for
community action in the field of water policy. Official Journal of the European
Communities L327/1:1-73.
European Commission, 2008. Commission Decision of 30 October 2008 establishing,
pursuant to Directive 2000/60/EC of the European Parliament and of the Council, the
values of the Member State monitoring system classifications as a result of the
intercalibration exercise. Official Journal of the European Union L332: 20-44.
European Communities, 2003. River and lakes – Typology, reference conditions and
classification systems. Common Implementation Strategy for the Water Framework
Directive (2000/60/EC). Guidance document No. 10. Office for Official Publications of
the European Communities, Luxembourg.
European Communities, 2005. Guidance on the intercalibration process 2004-2006.
Common Implementation Strategy for the Water Framework Directive (2000/60/EC).
Guidance document No. 14. Office for Official Publications of the European
Communities, Luxembourg.
Europäische Kommission, 2000. Richtlinie 2000/60/EG des Europäischen Parlaments
und des Rates vom 23. Oktober 2000 zur Schaffung eines Ordnungsrahmens für
Maßnahmen der Gemeinschaft im Bereich der Wasserpolitik. Amtsblatt der
Europäischen Gemeinschaften L 327/1: 1-73.
Feld, C.K. & D. Hering, 2007. Community structure or function: effects of environmental
stress on benthic macroinvertebrates at different spatial scales. Freshwater Biology 52:
1380–1399.
Ferreira, M.T., P.M. Rodríguez-González, F.C. Aguiar & A. Albuquerque, 2005.
Assessing biotic integrity in Iberian rivers: Development of a multimetric plant index.
Ecological Indicators 5: 137-149.
Friberg, N., L. Sandin, M. Furse, S.E. Larsen, R.T. Clark & P. Haase, 2006.
Comparison of macroinvertebrate sampling methods in Europe. In: M.T. Furse, D.
Hering, K. Brabec, A. Buffagni, L. Sandin and P.F.M. Verdonschot (Editors), The
111
References
ecological status of European rivers. Evaluation and intercalibration of assessment
methods. Hydrobiologia, 566: 365-378.
Friedrich, G., E. Coring & B. Küchenhoff, 1995. Vergleich verschiedener europäischer
Untersuchungs- und Bewertungsmethoden für Fließgewässer. Landesumweltamt
Nordrhein-Westfalen, Essen.
Friedrich, G. & V. Herbst, 2004. Eine erneute Revision des Saprobiensystems -
weshalb und wozu? Acta Hydrochimica et Hydrobiologica 32: 61-74.
Furse, M., D. Hering, O. Moog, P. Verdonschot, L. Sandin, K. Brabec, K. Gritzalis, A.
Buffagni, P. Pinto, N. Friberg, J. Murray-Bligh, J. Kokes, R. Alber, P. Usseglio-Polatera,
P. Haase, R. Sweeting, B. Bis, K. Szoszkiewicz, H. Soszka, G. Springe, F. Sporka & I.
Krno, 2006. The STAR project: context, objectives and approaches. In: M.T. Furse, D.
Hering, K. Brabec, A. Buffagni, L. Sandin and P.F.M. Verdonschot (Editors), The
ecological status of European rivers. Evaluation and intercalibration of assessment
methods. Hydrobiologia, 566: 3-29.
Gabriels, W., 2007. Multimetric assessment of freshwater macroinvertebrate
communities in Flanders, Belgium. PhD thesis. Ghent University, Ghent.
Ghetti, P. F. & G. Bonazzi, 1977. A comparison between various criteria for the
interpretation of biological data in the analysis of the quality of running waters. Water
Research 11: 819-831.
Ghetti, P. F. & G. Bonazzi, 1980. Biological water assessment methods: Torrente
Parma, Torrente Stirone, Fiume Po. 3rd Technical Seminar. Final Report. Commission
of the European Communities, Brussels.
Groffman, P., J. Baron, T. Blett, A. Gold, I. Goodman, L. Gunderson, B. Levinson, M.
Palmer, H. Paerl, G. Peterson, N. Poff, D. Rejeski, J. Reynolds, M. Turner, K.
Weathers & J. Wiens, 2006. Ecological thresholds: The key to successful
environmental management or an important concept with no practical application?
Ecosystems 9: 1-13.
Haase, P., J. Murray-Bligh, S. Lohse, S. Pauls, A. Sundermann, R. Gunn & R. Clarke,
2006. Assessing the impact of errors in sorting and identifying macroinvertebrate
samples. In: M.T. Furse, D. Hering, K. Brabec, A. Buffagni, L. Sandin and P.F.M.
Verdonschot (Editors), The ecological status of European rivers. Evaluation and
intercalibration of assessment methods. Hydrobiologia, 566: 505-521.
Hardin, G., 1968. The tragedy of the commons. Science 162: 1243-1248.
Hatton-Ellis, T., 2008. The Hitchhiker's Guide to the Water Framework Directive.
Aquatic Conservation-Marine and Freshwater Ecosystems 18: 111-116.
112
References
Heiskanen, A.-S., W. van de Bund, A.C. Cardoso & P. Nõges, 2004. Towards good
ecological status of surface waters in Europe - interpretation and harmonisation of the
concept. Water Science and Technology 49: 169-177.
Helešic, J., 2006. Biological monitoring of running waters in Eastern and Central
European countries (former Communist Block). In: G. Ziglio, M. Siligardi & G. Flaim
(Editors), Biological monitoring of rivers: applications and perspectives. John Wiley and
Sons, Chichester, pp. 327-350.
Hering, D., A. Buffagni, O. Moog, L. Sandin, M. Sommerhäuser, I. Stubauer, C.K. Feld,
R.K. Johnson, P. Pinto, N. Skoulikidis, P.F.M. Verdonschot & S. Zahrádková, 2003.
The development of a system to assess the ecological quality of streams based on
macroinvertebrates – design of the sampling programme within the AQEM project.
International Review of Hydrobiology 88: 345-361.
Hering, D., O. Moog, L. Sandin & P.F.M. Verdonschot, 2004. Overview and application
of the AQEM assessment system. Hydrobiologia 516: 1-20.
Hering, D., R.K. Johnson, S. Kramm, S. Schmutz, K. Szoszkiewicz & P.F.M.
Verdonschot, 2006a. Assessment of European rivers with diatoms, macrophytes,
invertebrates and fish: A comparative metric-based analysis. Freshwater Biology 51:
1757-1785.
Hering, D., C.K. Feld, O. Moog & T. Ofenböck, 2006b. Cook book for the development
of a Multimetric Index for biological condition of aquatic ecosystems: experiences from
the European AQEM and STAR projects and related initiatives. In: M.T. Furse, D.
Hering, K. Brabec, A. Buffagni, L. Sandin and P.F.M. Verdonschot (Editors), The
ecological status of European rivers. Evaluation and intercalibration of assessment
methods. Hydrobiologia, 566: 311-324.
Holmes, N.T.H. & B.A. Whitton, 1975. Macrophytes of the river Tweed. Transactions of
the Botanical Society of Edinburgh 42: 369-381.
Holmes, N.T.H., J.R. Newman, S. Chadd, K.J. Rouen, L. Saint & F.H. Dawson, 1999.
Mean Trophic Rank: A User's Manual. R & D Technical Report E38. Environment
Agency, Bristol.
Hume, D., 1978. A treatise of human nature. Oxford University Press, Oxford.
ICPDR (International Commission for the Protection of the Danube River), 2004. Water
quality in the Danube River Basin - TNMN yearbook 2001. ICPDR, Vienna.
Illies, J. (Editor), 1967. Limnofauna Europaea. G. Fischer, Stuttgart.
Janauer, G.A., 2001. Is what has been measured of any direct relevance to the
success of the macrophyte in its particular environment? Journal of Limnology 60
(Suppl.): 33-38.
113
References
Janauer, G.A., P. Hale & R. Sweeting (Editors), 2003. Macrophyte inventory of the river
Danube: A pilot study. Archiv für Hydrobiologie, Supplement “Large Rivers” 147 (1-2):
1-229.
Just, I., F. Schöll & T. Tittitzer, 1998. Versuch einer Harmonisierung nationaler
Methoden zur Bewertung der Gewässergüte im Donauraum am Beispiel der Abwässer
der Stadt Budapest. Umweltbundesamt, Berlin.
Kant, I., 1800. Immanuel Kants Logik. Ein Handbuch zu Vorlesungen. Friedrich
Nicolovicus, Königsberg.
Kelly, M.G. & B.A. Whitton, 1998. Biological monitoring of eutrophication in rivers.
Hydrobiologia 384: 55-67.
Kelly, M., C. Bennett, M. Coste, C. Delgado, F. Delmas, L. Denys, L. Ector, C. Fauville,
M. Ferréol, M. Golub, A. Jarlman, M. Kahlert, J. Lucey, B. Ní Chatháin, I. Pardo, P.
Pfister, J. Picinska-Faltynowicz, J. Rosebery, C. Schranz, J. Schaumburg, H. van Dam
& S. Vilbaste, 2008. A comparison of national approaches to setting ecological status
boundaries in phytobenthos assessment for the European Water Framework Directive:
results of an intercalibration exercise. Hydrobiologia. DOI 10.1007/s10750-008-9641-4
Knoben, R.A.E., C. Roos & M.C.M. van Oirschot, 1995. Biological assessment
methods for watercourses. UN/ECE Task Force on Monitoring and Assessment,
Lelystad.
Knoben, R.A.E., L. Bijlmakers & P. van Meenen, 1999. Water Quality Enhancement in
the Danube River Basin; sub action 2A: Water quality classification/characterisation.
IWACO, 's-Hertogenbosch.
Kohler, A., 1978. Methoden der Kartierung von Flora und Vegetation von
Süßwasserbiotopen. Landschaft & Stadt 10: 73-85.
Korte, T. & K. van de Weyer, 2005. Die Bewertung von Fließgewässern mit
Makrophyten gemäß EU-WRRL - Ergebnisse des Vergleichs von zwei
Bewertungsverfahren. Wasser und Abfall 9/2005: 46-49.
Kownacki, A., H. Soszka, D. Kudelska & T. Fleituch, 2004. Bioassessment of Polish
rivers based on macroinvertebrates. In Geller, W. et al. (Editors), Proceedings of the
international 11th Magdeburg Seminar on Waters in Central and Eastern Europe:
Assessment, Protection, Management. 18-22 October 2004, UFZ Leipzig: 250-251.
Lacoul, P. & B. Freedman, 2006. Environmental influences on aquatic plants in
freshwater ecosystems. Environmental Reviews 14: 89-136.
LAWA-AO, 2007. RaKon Monitoring Teil B. Arbeitspapier II: Hintergrund- und
Orientierungswerte für physikalisch-chemische Komponenten. Stand 07.03.2007.
114
References
Ständiger Ausschuss "Oberflächengewässer und Küstengewässer" der Bund/Länder-
Arbeitsgemeinschaft Wasser, Mainz.
Leyssen, A., P. Adriaens, L. Denys, J. Packet, A. Schneiders, K. Van Looy & L.
Vanhecke, 2005. Toepassing van verschillende biologische beoordelingssystemen op
Vlaamse potentiële interkalibratielocaties overeenkomstig de Europese kaderrichtlijn
water : partim 'Macrofyten'. Instituut voor Natuurbehoud, Brussels.
Lorenz, A., D. Hering, C.K. Feld, C.K. & P. Rolauffs, 2004. A new method for assessing
the impact of hydromorphological degradation on the macroinvertebrate fauna of five
German stream types. Hydrobiologia 516: 107-127.
Meilinger, P., S. Schneider & A. Melzer, 2005. The reference index method for the
macrophyte-based assessment of rivers – a contribution for the implementation of the
European Water Framework Directive in Germany. International Review of
Hydrobiology 90: 322-342.
Melzer, A., R. Harlacher, K. Held, R. Sirch & E. Vogt, 1986. Die Makrophytenvegetation
des Chiemsees. Informationsbericht des Bayerischen Landesamts für
Wasserwirtschaft 4/86. BLfW, München.
Metcalfe-Smith, J.L., 1994. Biological water-quality assessment of rivers: Use of
macroinvertebrate communities. In Calow, P. & G.E. Petts (Editors), The Rivers
Handbook - hydrological and ecological principles. Blackwell Scientific Publications,
Oxford: 144-170.
MMGA (Ministeriul Mediului si Gospodaririi Apelor), 2006. Anexa la Ordinul ministrului
mediului si gospodaririi apelor nr. 161/2006 pentru aprobarea Normativului privind
clasificarea calitaii apelor de suprafata in vederea stabilirii starii ecologice a corpurilor
de apa. Ministry of Environment and Water Management, Bucharest.
Molen, D. T. van der, M. Beers, M.S. v. d. Berg, T. v. d. Broek, R. Buskens, H.C.
Coops, H. v. Dam, G. Duursema, M. Fagel, T. Ietswaart, M. Klinge, R.A.E. Knoben, J.
Kranenbarg, J. d. Leeuw, R. Noordhuis, R.C. Nijboer, R. Pot, P.F.M. Verdonschot & T.
Vriese, 2004. Referenties en maatlatten voor rivieren ten behoeve van de Kaderrichtlijn
Water - version July 2004. Alterra, Wageningen.
Moog, O., A. Chovanec, J. Hinteregger & A. Römer, 1999. Richtlinie zur Bestimmung
der saprobiologischen Gewässergüte von Fliessgewässern. Bundesministerium für
Land- und Forstwirtschaft, Wien.
Morpurgo, M., 1996. Confronto fra Indice Saprobico (Friedrich e DIN, 1990) e Indice
Biotico Esteso (Ghetti e IRSA, 1995). Biologia Ambientale 14: 30-36.
Moss, B. 2007. Shallow lakes, the water framework directive and life. What should it all
be about? Hydrobiologia 584: 381-394.
115
References
National Rivers Authority, 1994. The quality of rivers and canals in England and Wales
(1990 to 1992) as assessed by a new general quality assessment scheme. HMSO,
London.
Newman, P.J., 1988. Classification of surface water quality. Review of schemes used
in EC member states. Heinemann Professional Publishing Ltd., Oxford.
NF T90-395, 2003. Water quality - Determination of the Macrophytes biological index
for rivers (IBMR). Association Française de Normalisation (AFNOR), Saint Denis La
Plaine.
Nieuwenhuis, R., 2005. ECOSURV Manual for Sampling and Determination. Hungarian
Ministry for Environment and Water, Budapest.
Nixon, S.C., C.P. Mainstone, T. Moth Iversen, P. Kristensen, E. Jeppesen, N. Friberg,
E. Papathanassiou, A. Jensen & F. Pedersen, 1996. The harmonized monitoring and
classification of ecological quality of surface waters in the European Union. Final
Report. European Commission Directorate General XI, Brussels.
ÖNORM M6232:1997. Richtlinien für die ökologische Untersuchung und Bewertung
von Fließgewässern. Österreichisches Normungsinstitut, Wien.
Owen, R., C. Bennett, S. Birk, A. Buffagni, S. Erba, N. Mengin, J. Murray-Bligh, G.
Ofenböck, I. Pardo, W. van de Bund, F. Wagner & J.-G. Wasson, 2010. Intercalibration
of ecological class boundaries for different European river macro-invertebrate
assessment methods used to implement the Water Framework Directive. Submitted to
Hydrobiologia.
Paal, J. & T. Trei, 2004. Vegetation of Estonian watercourses; the drainage basin of the
southern coast of the Gulf of Finland. Annales Botanici Fennici 41: 157-177.
Pall, K., Moser, V., Schaumburg, J., Schranz, C., & P. Meilinger, 2005. Ergebnisse zur
Interkalibrierung der Fließgewässerbewertung mit Makrophyten (Option 3: Vergleich
Deutschland-Österreich). Oral presentation held at the conference of the “Deutsche
Gesellschaft für Limnologie” in Karlsruhe, 28 September 2005.
Pantle, R. & H. Buck, 1955. Die biologische Überwachung der Gewässer und die
Darstellung der Ergebnisse. Gas- und Wasserfach 96: 604.
Pielou, E.C., 1966. The measurement of diversity in different types of biological
collections. Journal of Theoretical Biology 13: 131-144.
Pollard, P. & W. van de Bund, 2005. Template for the development of a boundary
setting protocol for the purposes of the intercalibration exercise. Common
Implementation Strategy - Working Group A ECOSTAT. Version 1.2.
116
References
Pot, R., 2005. QBWat - ecologische beoordeling van waterkwaliteit conform de
Europese Kaderrichtlijn Water. Version 1.01.
Rico, E., A. Rallo, M.A. Sevillano & M.L. Arretxe, 1992. Comparison of several
biological indices based on river macroinvertebrate benthic community for assessment
of running water quality. Annales de Limnologie 28: 147-156.
Rolauffs, P., D. Hering, M. Sommerhäuser, S. Rödiger & S. Jähnig, 2003. Entwicklung
eines leitbildorientierten Saprobienindexes für die biologische
Fließgewässerbewertung. Umweltbundesamt, Berlin.
Rothschein, J., 1962. Saprobiologische Charakteristik der fließenden Gewässer im
Einzugsgebiete des Flusses Bodrog auf der Basis von Zoobenthosanalysen.
Technology of Water (Institute Chemical Technology, Prague) 6: 227-275.
Rott, E., G. Hofmann, K. Pall, P. Pfister & E. Pipp, 1997. Indikationslisten für
Aufwuchsalgen in Österreichischen Fliessgewässern, Teil 1: Saprobielle Indikation.
Bundesministerium für Land- und Forstwirtschaft, Wasserwirtschaftskataster, Wien.
Rott, E., P. Pfister, H. van Dam, E. Pipp, K. Pall, N. Binder, N. & K. Ortler, 1999.
Indikationslisten für Aufwuchsalgen in Österreichischen Fliessgewässern, Teil 2:
Trophieindikation und autökologische Anmerkungen. Bundesministerium für Land- und
Forstwirtschaft, Wasserwirtschaftskataster, Wien.
Sandin, L. & D. Hering, 2004. Comparing macroinvertebrate indices to detect organic
pollution across Europe: a contribution to the EC Water Framework Directive
intercalibration. Hydrobiologia 516: 55-68.
Schaumburg, J., C. Schranz, J. Foerster, A. Gutowski, G. Hofmann, P. Meilinger, S.
Schneider & U. Schmedtje, 2004. Ecological classification of macrophytes and
phytobenthos for rivers in Germany according to the Water Framework Directive.
Limnologica 34: 283-301.
Schaumburg, J., U. Schmedtje, B. Köpf, C. Schranz, S. Schneider, P. Meilinger, D.
Stelzer, G. Hofmann, A. Gutowski & J. Foerster, 2005. Makrophyten und Phytobenthos
in Flüssen und Seen. Leitbildbezogenes Bewertungsverfahren zur Umsetzung der EG-
Wasserrahmenrichtlinie. Informationsbericht Heft 1/05. Bayerisches Landesamt für
Wasserwirtschaft, München.
Schaumburg, J., C. Schranz, D. Stelzer, G. Hofmann, A. Gutowski & J. Foerster, 2006.
Instruction Protocol for the ecological Assessment of Running Waters for
Implementation of the EC Water Framework Directive: Macrophytes and Phytobenthos.
Bavarian Water Management Agency, Munich.
117
References
Schmedtje, U. (Editor), 2005. The Danube River Basin District. Part A - Basin-wide
overview (WFD Roof Report 2004). International Commission for the Protection of the
Danube River, Vienna.
Schmidt-Kloiber, A., A. Lorenz & W. Graf, 2006. The AQEM/STAR taxalist - a pan-
European macro-invertebrate ecological database and taxa inventory. In: M.T. Furse,
D. Hering, K. Brabec, A. Buffagni, L. Sandin and P.F.M. Verdonschot (Editors), The
ecological status of European rivers. Evaluation and intercalibration of assessment
methods. Hydrobiologia, 566: 325-342.
Schneider, S., 2000. Entwicklung eines Makrophytenindex zur Trophieindikation in
Fließgewässern. Shaker Verlag, Aachen.
Shannon, C.E. & W. Weaver, 1949. Mathematical theory of communication. University
of Illinois Press, Urbana.
Simpson, E. H., 1949. Measurement of diversity. Nature 163: 688.
Skriver, J., N. Friberg & J. Kirkegaard, 2000. Biological assessment of running waters
in Denmark: Introduction of the Danish Stream Fauna Index (DSFI). Verhandlungen
der Internationalen Vereinigung für theoretische und angewandte Limnologie 27: 1822-
1830.
Sládeček, V., 1973. System of water quality from the biological point of view. Archiv für
Hyrdrobiologie Beihefte (Ergebnisse der Limnologie) 7: 1-218.
Sporka, F., H. E. Vlek, E. Bulánková & I. Krno, 2006. Influence of seasonal variation on
bioassessment of streams using macroinvertebrates. In: M.T. Furse, D. Hering, K.
Brabec, A. Buffagni, L. Sandin and P.F.M. Verdonschot (Editors), The ecological status
of European rivers. Evaluation and intercalibration of assessment methods.
Hydrobiologia, 566: 543-555.
Steyaert, P. & G. Ollivier, 2007. The European Water Framework Directive: How
ecological assumptions frame technical and social change. Ecology and Society 12:
25.
STN (Slovenská Technická Norma) 83 0532-1 to 8, 1978/79. Biologický rozbor
povrchovej vody. (Biological analysis of surface water quality.) Slovak Standardisation
Institute, Bratislava.
Stubauer, I. & O. Moog, 2000. Taxonomic sufficiency versus need for information -
comments based on Austrian experience in biological water quality monitoring.
Internationale Vereinigung für theoretische und angewandte Limnologie:
Verhandlungen 27: 1-5.
Swedish Environmental Protection Agency, 2000. Environmental quality criteria: Lakes
and watercourses. Swedish Environmental Protection Agency, Stockholm.
118
References
SYSTAT Software Inc., 2002. TableCurve 2D - Version 5.01. SSI, Richmond CA.
Szoszkiewicz, K., T. Ferreira, T. Korte, A. Baattrup-Pedersen, J. Davy-Bowker & M.
O’Hare, 2006a. European river plant communities: the importance of organic pollution
and the usefulness of existing macrophyte metrics. In: M.T. Furse, D. Hering, K.
Brabec, A. Buffagni, L. Sandin and P.F.M. Verdonschot (Editors), The ecological status
of European rivers. Evaluation and intercalibration of assessment methods.
Hydrobiologia, 566: 211-234.
Szoszkiewicz K., J. Zbierska, S. Jusik, T. Zgoła, 2006b. Development of the
methodological basis for the biological monitoring of water bodies using macrophytes
and its application to water bodies of certain categories and types. Second phase,
volume 2: Rivers. Institute of Environmental Protection, Agricultural Academy "A.
Cieszkowicz", Warsaw. [in Polish]
Tansley, A.G., 1946: Introduction to plant ecology. Allen & Unwin, London.
Thiebaut, G., F. Guérold & S. Muller, 2002. Are trophic and diversity indices based on
macrophyte communities pertinent tools to monitor water quality? Water Research 36:
3602-3610.
Tittizer, T., 1976. Comparative study of biological-ecological water assessment
methods. Practical demonstration on the river Main. 2-6 June, 1975 (summary report).
In Amavis, R.-J. (Editor), Principles and methods for determining ecological criteria on
hydrobiocoenosis: Proceedings of the European Scientific Colloquium Luxembourg,
Nov. 1975. Pergamon Press, Oxford: 403-463.
Uzunov, J., 1979. Aquatic Oligochaeta - a supplement to the list of limnosaprobic
bioindicators. Doklady Bolgarskoi Akademii Nauk 32: 1101-1103.
Valsangiacomo, A., 1998. Die Natur der Ökologie: Anspruch und Grenzen ökologischer
Wissenschaften. Hochschulverlag, ETH Zürich, Zürich.
Van de Weyer, K., 2003. Kartieranleitung zur Erfassung und Bewertung der
aquatischen Makrophyten der Fließgewässer in Nordrhein-Westfalen gemäß den
Vorgaben der EU-Wasser-Rahmenrichtlinie. LUA-Merkblätter Nr. 39.
Landesumweltamt (LUA) NRW, Düsseldorf.
Van den Berg, M.S., H.C. Coops, R. Pot, W. Altenburg, R. Nijboer, T. v. d. Broek, M.
Fagel, G. Arts, R. Bijkerk, H. v. Dam, T. Ietswaart, J. v. d. Molen, K. Wolfstein, D. d.
Jong & H. Hartholt, 2004. Achtergronddocument referenties en maatlatten waterflora.
RIZA, Lelystad.^
Vlek, H. E., F. Sporka & I. Krno, 2006. Influence of macroinvertebrate sample size on
bioassessment of streams. In: M.T. Furse, D. Hering, K. Brabec, A. Buffagni, L. Sandin
119
References
and P.F.M. Verdonschot (Editors), The ecological status of European rivers. Evaluation
and intercalibration of assessment methods. Hydrobiologia, 566: 523-542.
White, L. T., 1967. The historical roots of our ecologic crisis. Science 155: 1203-1207.
Wiegleb, G., 1984. A study of habitat conditions of the macrophytic vegetation in
selected river systems in Western Lower Saxony (Federal Republic of Germany).
Aquatic Botany 18: 313-352.
Wiegleb, G., 1988. Analysis of flora and vegetation in rivers: concepts and applications.
In Symoens, J.J. (Editor), Vegetation of inland waters. Kluwer Academic Publishers,
Dordrecht: 311-340.
Wiegleb, G., 1991. Die Lebens- und Wuchsformen der makrophytischen
Wasserpflanzen und deren Beziehung zur Ökologie, Verbreitung und
Vergesellschaftung der Arten. Tuexenia 11: 135-147.
Willby, N., J. Hilton, J.-A. Pitt & G. Philipps, 2006. Summary of approach used in
LEAFPACS for defining ecological quality of rivers and lakes using macrophyte
composition. Interim Report June 2006. University of Stirling, Stirling.
Willby, N., J.-A. Pitt & G. Philipps, 2008. Development of a system for the classification
of lakes and rivers in the UK using aquatic macrophytes. Part II, Rivers. Scientific
report. University of Stirling, Stirling.
Woodiwiss, F.S., 1978. Comparative study of biological-ecological water quality
assessment methods. Second practical demonstration. Summary Report. Commission
of the European Union, Brussels.
Wright, J.F., D.W. Sutcliffe & M.T. Furse (Editors), 2000. Assessing the biological
quality of fresh waters: RIVPACS and other techniques. Freshwater Biological
Association, Ambleside.
Zelinka, M. & P. Marvan, 1961. Zur Präzisierung der biologischen Klassifikation der
Reinheit fließender Gewässer. Archiv für Hydrobiologie 57: 389-407.
120
Appendix: mICM indicator taxa scores
121
Appendix: Common type-specific mICM indicator taxa scores analysed in Chapter 3
Taxon name Aquaticity mICM 1x2 mICM 3 mICM 4x2 Acorus calamus L. 4 - - 0.021 Agrostis stolonifera L. 4 0.086 -0.421 -0.079 Alisma lanceolatum With. 4 0.053 - -0.213 Alisma plantago-aquatica L. 4 -0.184 - 0.169 Amblystegium fluviatile (Hedw.) Schimp. 1 - -0.086 0.323 Amblystegium riparium (Hedw.) B.S.G. 2 -0.091 -0.866 0.153 Amblystegium tenax (Hedw.) C. E. O. Jensen 1 - 0.008 - Aneura pinguis (L.) Dumort. 2 - -0.004 - Angelica sylvestris L. 5 -0.139 - -0.105 Apium nodiflorum (L.) Lag. 2 0.198 -0.145 - Audouinella sp. Bory 1 - 0.034 - Batrachospermum sp. Roth 1 - -0.034 - Berula erecta (Huds.) Coville 2 -0.011 - 0.160 Bidens cernua L. 5 0.109 - -0.170 Bidens frondosa L. 5 0.045 - 0.086 Bidens tripartita L. 5 -0.293 - -0.056 Brachythecium plumosum (Hedw.) B.S.G. 1 - 0.570 - Brachythecium rivulare Schimp. 2 - 0.388 0.277 Butomus umbellatus L. 4 -0.195 - -0.125 Caltha palustris L. 4 0.450 0.142 0.038 Callitriche cophocarpa Sendtn. 1 -0.295 -0.070 0.007 Callitriche hamulata Kuetz. ex W.D.J. Koch 1 1.000 0.014 0.336 Callitriche obtusangula Le Gall 1 0.125 -0.277 -0.183 Callitriche palustris L. 1 0.231 - - Callitriche platycarpa Kuetz. 1 0.193 -0.280 0.236 Callitriche stagnalis Scop. 1 0.202 -0.121 - Cardamine amara L. 5 0.467 -0.067 0.076 Carex rostrata Stokes 4 0.144 -0.050 0.332 Carex vesicaria L. 4 - - -0.085 Ceratophyllum demersum L. 1 -0.205 -0.291 -0.492 Chara sp. L. ex Vaillant 1 - - 0.190 Chiloscyphus polyanthos (L.) Corda. 1 - 0.595 - Cinclidotus fontinaloides (Hedw.) P. Beauv. 1 - -0.172 - Cladophora glomerata (L.) Kuetz. 1 - -0.228 -0.070 Cladophora sp. Kuetz. 1 -0.197 -0.428 -0.198 Collema fluviatile (Huds.) Steud. 3 - -0.104 - Conocephalum conicum (L.) Dum. 5 - 0.139 - Cratoneuron filicinum (Hedw.) Spruce 1 - -0.109 - Dermatocarpon sp. Eschw. 3 - 0.159 -
Appendix: mICM indicator taxa scores
Taxon name Aquaticity mICM 1x2 mICM 3 mICM 4x2 Diatoma sp. Lyngb. 1 - -0.100 -0.242 Draparnaldia sp. Bory de St Vincent 1 - 0.166 - Drepanocladus aduncus (Hedw.) Warnst. 3 - 0.125 - Eleocharis acicularis (L.) Roem & Schult 5 0.202 - - Eleocharis palustris (L.) Roem & Schult 4 -0.096 -0.129 -0.102 Elodea canadensis Michx. 1 -0.152 -0.138 0.027 Elodea nuttallii (Planch.) H. St. John 1 -0.267 -0.286 -0.543 Enteromorpha sp. Link 1 - - -0.331 Epilobium hirsutum L. 5 0.092 -0.215 -0.301 Epilobium palustre L. 5 0.068 - -0.145 Equisetum arvense L. 5 -0.084 -0.202 - Equisetum fluviatile L. 2 0.207 -0.041 0.434 Equisetum palustre L. 2 0.179 -0.145 0.009 Eupatorium cannabinum L. 5 -0.109 -0.076 -0.054 Fissidens crassipes Wils. ex B.S.G. 1 - -0.046 -0.071 Fissidens pusillus (Wils.) Milde 2 - 0.080 - Fissidens rivularis (Spruce) B.S.G. 2 - -0.023 - Fissidens rufulus B.S.G. 2 - 0.218 - Fontinalis antipyretica Hedw. 1 0.018 -0.413 0.933 Fontinalis squamosa Hedw. 1 - 0.525 - Galium palustre L. 4 -0.170 -0.173 -0.140 Glyceria aquatica (L.) Wahlb. 4 -0.421 -0.203 -0.316 Glyceria fluitans (L.) R. Br. 2 0.192 -0.039 0.345 Hildenbrandia sp. Nardo 1 -0.043 -0.060 0.795 Hottonia palustris L. 1 0.087 - - Hydrocharis morsus-ranae L. 1 -0.174 - 0.085 Hygrohypnum duriusculum (De Not.) Jamieson 2 - -0.010 - Hygrohypnum luridum (Hedw.) Jenn. 2 - 0.292 - Hygrohypnum ochraceum (Wils.) Loeske 1 - 0.501 - Hydrodictyon sp. Roth 1 - - -0.304 Hyocomium armoricum (Brid.) Wijk & Marg. 3 - 0.559 - Hydrocotyle ranunculoides L. 5 -0.354 - - Hydrurus sp. C.A. Agardh 1 - 0.102 - Iris pseudacorus L. 4 0.083 -0.182 -0.007 Isothecium myosuroides Brid. 2 - 0.249 - Juncus acutiflorus Ehrh. ex Hoffm. 5 - -0.127 - Juncus articulatus L. 5 0.156 0.110 0.076 Juncus bufonius L. 5 - - -0.032 Juncus bulbosus L. 4 - 0.170 - Juncus conglomeratus L. 5 - 0.128 - Juncus effusus L. 4 -0.134 -0.123 -0.093 Lemanea sp. Bory de St Vincent 1 - 0.173 - Leersia oryzoides (L.) Sw. 5 - - 0.181 Lemna gibba L. 1 -0.001 - -0.369 Lemna minor L. 1 -0.735 -0.410 -0.581
122
Appendix: mICM indicator taxa scores
Taxon name Aquaticity mICM 1x2 mICM 3 mICM 4x2 Lemna minuta Kunth 1 -0.521 - -0.211 Lemna trisulca L. 1 -0.106 - 0.153 Littorella uniflora (L.) Asch. 1 - 0.078 - Lunularia cruciata (L.) Dum. 5 - -0.224 - Luronium natans (L.) Rafin. 2 0.086 - - Lycopus europaeus L. 4 0.096 -0.218 0.001 Lyngbya sp. C.A. Agardh ex Gomont 1 - 0.052 - Lysimachia nummularia L. 5 - -0.009 - Lysimachia thyrsiflora L. 4 - - 0.370 Lysimachia vulgaris L. 5 0.070 -0.108 0.067 Lythrum salicaria L. 5 -0.121 -0.154 -0.052 Marchantia polymorpha L. 5 - 0.099 - Marsupella emarginata (Ehrh.) Dum. 2 - 0.426 - Melosira sp. C.A. Agardh 1 - -0.293 -0.228 Mentha aquatica L. 4 0.195 -0.232 0.558 Mentha longifolia (L.) Huds. em. Harley 4 - -0.212 - Microspora sp. Balbiani 1 - -0.097 - Mnium hornum Hedw. 2 - 0.321 - Montia fontana L. 2 - 0.108 - Mougeotia sp. C.A. Agardh 1 - 0.225 - Myosotis scorpioides L. 2 0.050 -0.249 -0.139 Myriophyllum alterniflorum DC. 1 0.233 0.120 - Myriophyllum aquaticum (Vell.) Verdc. 1 -0.030 - -0.204 Myriophyllum spicatum L. 1 -0.159 -0.321 -0.092 Myriophyllum verticillatum L. 1 0.078 -0.200 - Nasturtium officinale R. Br. 2 -0.014 0.007 -0.181 Nitella flexilis (L.) C.A. Agardh 1 0.134 - - Nitella sp. C.A. Agardh 1 0.205 - - Nostoc sp. Vaucher ex Born& & Flahault 1 - 0.025 - Nuphar lutea (L.) Sibth. & Sm. 1 -0.260 -0.206 0.030 Nymphoides peltata (Gmel.) Kuntze 1 -0.308 - - Octodiceras fontanum (La Pyl.) Lindb. 1 - - -0.083 Oedogonium sp. Link 1 - -0.398 -0.546 Oenanthe aquatica (L.) Poiret 1 0.179 - -0.223 Oenanthe crocata L. 2 - 0.103 - Oscillatoria sp. Vaucher ex Gomont 1 - 0.030 -0.401 Pellia endiviifolia (Dicks) Dumort 2 0.301 -0.002 0.268 Pellia epiphylla L. Corda 2 - 0.598 - Petasites hybridus (L.) Gaertn., Mey. & Scherb. 5 - -0.037 - Peucedanum palustre (L.) Moench 5 0.029 - 0.223 Phalaris arundinacea L. 4 0.052 -0.540 -0.284 Philonotis caespitosa Jur. 2 - 0.219 - Philonotis gr. fontana (Hedw.) Brid. 1 - 0.191 - Phormidium sp. Kuetz. ex Gomont 1 - 0.127 - Phragmites australis (Cav.) Trin. ex Steud 4 0.364 - -0.167
123
Appendix: mICM indicator taxa scores
Taxon name Aquaticity mICM 1x2 mICM 3 mICM 4x2 Plagiomnium rostratum (Schrad.) T.Kop. 3 - 0.012 - Plagiomnium undulatum (Hedw.) Kop. 3 - 0.199 - Polygonum amphibium L. 2 -0.191 -0.168 -0.246 Polygonum hydropiper L. 4 0.181 -0.319 0.087 Potamogeton alpinus Balbis 1 0.348 - 0.566 Potamogeton berchtoldii Fieber 1 -0.222 - 0.038 Potamogeton crispus L. 1 -0.333 -0.299 -0.444 Potamogeton lucens L. 1 - - 0.083 Potamogeton natans L. 1 0.029 -0.185 0.053 Potamogeton obtusifolius Mert. & Koch 1 -0.044 - 0.213 Potamogeton panormitanus Biv. 1 -0.004 - -0.006 Potamogeton pectinatus L. 1 -0.740 - -1.000 Potamogeton perfoliatus L. 1 -0.541 - 0.186 Potamogeton polygonifolius Pourret 1 0.134 0.097 - Potamogeton praelongus Wulfen 1 - - 0.325 Potamogeton trichoides Cham. & Schltdl 1 -0.514 - -0.315 Racomitrium aciculare (Hedw.) Brid. 3 - 0.788 - Ranunculus aquatilis L. 1 - -0.022 0.358 Ranunculus circinatus Sibth. 1 0.051 - -0.084 Ranunculus flammula L. 4 - 0.340 - Ranunculus fluitans Lamk. 1 - -0.147 0.099 Ranunculus lingua L. 5 0.287 - 0.160 Ranunculus omiophyllus Ten. 1 - 0.009 - Ranunculus peltatus Schrank 1 0.230 -0.100 0.242 Ranunculus penicillatus (Dumort.) Bab. 1 0.042 -0.302 -0.224 Ranunculus penicillatus (Dumort.) Bab. var. penicillatus 1 - -0.158 - Ranunculus penicillatus ssp. pseudofluitans (Syme) S.D. Webster 1 - -0.164 - Ranunculus sceleratus L. 5 0.075 - -0.295 Ranunculus trichophyllus (Chaix) Grey 1 - -0.245 0.301 Rhizoclonium sp. Kuetz. 1 - -0.330 -0.342 Rhynchostegium riparioides (Hedw.) Cardo 1 0.229 0.103 0.165 Rhizomnium punctatum (Hedw.) T. Kop. 3 - 0.107 - Riccardia chamedryfolia (With.) Grolle 2 - 0.097 - Riccia fluitans L. 2 -0.107 - -0.299 Rorippa amphibia (L.) Besser 4 -0.524 -0.077 -0.351 Rumex hydrolapathum Huds. 5 -0.043 - -0.244 Sagittaria sagittifolia L. 2 -0.247 - -0.571 Scapania undulata (L.) Dum 1 - 1.000 - Scirpus fluitans L. 1 0.217 - - Scirpus lacustris L. 1 - - 0.116 Scirpus sylvaticus L. 5 0.232 -0.166 0.027 Scrophularia auriculata L. 5 - - -0.051 Schistidium rivulare (Brid.) Podp. 3 - -0.062 - Scytonema sp. C.A. Agardh ex Bornet & Flahault 1 - 0.036 - Solanum dulcamara L. 5 -0.088 -0.293 -0.104
124
Appendix: mICM indicator taxa scores
Taxon name Aquaticity mICM 1x2 mICM 3 mICM 4x2 Sparganium emersum Rehmann 2 -0.445 -0.216 0.179 Sparganium emersum Rehmann f. longissimum 2 - -0.301 - Sparganium erectum L. 4 -0.164 -0.250 -0.032 Sphagnum sp. L. 2 - 0.333 - Spirogyra sp. Link 1 - -0.172 - Spirodela polyrhiza (L.) Schleid 1 -0.374 -0.266 -0.335 Stigeoclonium sp. Kuetz. 1 - -0.123 - Stigeoclonium tenue (C.A. Agardh) Kuetz. 1 - -0.112 - Tetraspora sp. Link ex Descaux 1 - 0.006 - Thamnobryum alopecurum (Hedw.) Gang. 2 - 0.249 - Thelypteris palustris (Gray) Schott 5 -0.110 - - Tolypothrix sp. Kuetz. ex Bornet & Flahault 1 - 0.041 - Tribonema sp. Drebes & Solier 1 - 0.044 - Typha angustifolia L. 4 -0.199 - - Typha latifolia L. 4 -0.141 -0.153 -0.243 Ulothrix sp. Kuetz. 1 - -0.078 - Utricularia sp. L. 1 -0.232 - - Utricularia vulgaris L. 1 -0.171 - - Vaucheria sp. DC. 2 - -0.272 -0.173 Veronica anagallis-aquatica L. 2 0.106 -0.157 0.388 Veronica beccabunga L. 2 0.184 -0.338 0.161 Verrucaria sp. F.H. Wigg. 3 - 0.008 - Zannichellia palustris L. 1 - - -0.314
125
Lebenslauf
Lebenslauf
Persönliche Daten
Name: Sebastian Birk
Geburtsdatum: 10. April 1974
Geburtsort: Bottrop
Anschrift: Hüttengasse 23, Hamm (Sieg)
Familienstand: verheiratet, 3 Kinder
Ausbildung und Berufstätigkeit
Seit 08/03 - Wissenschaftlicher Mitarbeiter: Universität Duisburg Essen, FB
Biologie & Geographie, Abteilung Hydrobiologie; Mitarbeit an
verschiedenen Forschungsprojekten zur Umsetzung der EG-
Wasserrahmenrichtlinie
08/03 - Abschluss, Universität Duisburg-Essen: Diplom-
Umweltwissenschaftler (Note: sehr gut)
01/03 – 08/03 - Diplomarbeit Universität Duisburg-Essen: 'Review of
European assessment methods for rivers and streams'. Beitrag zu EG-
Forschungsprojekt (Note: 1,1)
09/95 – 08/03 - Universität Duisburg-Essen: Studium der Ökologie, Biologie
und Philosophie
01/95 – 09/95 - Reisen im Europäischen Ausland sowie mehrwöchige
Auftrittstournee in Deutschland (Musik)
10/93 – 12/94 - Zivildienst beim Sozialdienst Katholischer Männer, Bottrop.
09/84 – 07/93 - Josef-Albers-Gymnasium Bottrop; Abschluss Abitur
(Note: 2,0)
08/80 – 07/84 - Droste-Hülshoff Grundschule Bottrop
Erklärungen
Erklärung
Hiermit erkläre ich, gem. § 6 Abs. 2, Nr. 6 der Promotionsordnung der Math.-Nat.-
Fachbereiche zur Erlangung des Dr. rer. nat., dass ich die vorliegende Dissertation
selbständig verfasst und mich keiner anderen als der angegebenen Hilfsmittel bedient
habe.
Essen, den 9. April 2009
Sebastian Birk
Erklärung
Hiermit erkläre ich, gem. § 6 Abs. 2, Nr. 7 der Promotionsordnung der Math.-Nat.-
Fachbereiche zur Erlangung der Dr. rer. nat., dass ich das Arbeitsgebiet, dem das
Thema „Intercalibration of national methods to assess the ecological quality of rivers in
Europe using benthic invertebrates and aquatic flora“ zuzuordnen ist, in Forschung und
Lehre vertrete und den Antrag von Herrn Sebastian Birk befürworte.
Essen, den 9. April 2009
Prof. Dr. Daniel Hering
Erklärung
Hiermit erkläre ich, gem. § 6 Abs. 2, Nr. 8 der Promotionsordnung der Math.-Nat.-
Fachbereiche zur Erlangung des Dr. rer. nat., dass ich keine anderen Promotionen
bzw. Promotionsversuche in der Vergangenheit durchgeführt habe und dass diese
Arbeit von keiner anderen Fakultät abgelehnt worden ist.
Essen, den 9. April 2009
Sebastian Birk